AI Engineer jobs in Israel

Description You'll design the architecture that lets AI run compliance at scale. Sedric is the AI compliance platform for financial services. Our agentic AI automates oversight across customer communications and marketing — real-time guardrails on calls, pre-approval review on every marketing asset, and post-publication monitoring across partners and channels. Because every customer gets a dedicated compliance model, accuracy goes up, false positives go down, and compliance teams move faster without taking on more risk. AI isn’t a feature at Sedric — it’s the product. Every agent, LLM flow, and retrieval pipeline that runs a customer’s compliance program runs on backend systems someone has to design, build, and keep fast, accurate, and cost-efficient at scale. We’re looking for a hands-on AI engineer who designs those systems and writes the code. You’ll own the architecture of our AI backend end to end, ship it to production, monitor how it performs with real customers, and raise the bar for the engineers around you through code reviews, design reviews, and mentoring. The mission? We're at an inflection point. Enterprise financial services clients are signing on, and they need more than a product — they need a platform. That means a unified LLM strategy, an architecture that scales, and an R&D org that moves with the same urgency as the business. This role reports to the AI team Dev Team Lead and is based in Tel Aviv (hybrid model). This is a hands-on engineering role. It’s not a research position and not a people-management role. You’ll spend most of your time designing and building production systems. What You’ll Own You'll own Sedric's AI reference architecture end to end — the patterns, standards, and platform capabilities that every AI initiative across engineering builds on. You'll lead architecture reviews, set the technology roadmap, and make the call on what we adopt, pilot, or retire. • Design and build the backend architecture for Sedric’s AI agents, LLM pipelines, and retrieval systems, and write a large share of the production code yourself • Take AI capabilities from prototype to production in a multi-tenant SaaS environment • Optimize for scale and cost: model selection, prompt and token efficiency, caching, batching, latency, and infrastructure spend • Build monitoring and evaluation for AI quality in production (accuracy, false positives, drift, cost per customer) and act on what it shows • Set engineering standards for AI development and mentor engineers through pairing, code reviews, and design reviews • Bring new AI techniques into the product when they solve a real customer problem, and prove it in production Requirements You're a fit if… • You have 5+ years of ML/AI architecture experience in a SaaS company • 3+ Backend development experience • You bring both the technical depth and the leadership range this role demands. • You've built agentic systems with tool use, planning, and multi-step reasoning in production, not just in a notebook • You've set up AI governance and evaluation harnesses from scratch • You have proven, hands-on experience with AI in production systems • You can take a project from concept to shipped and interface with stakeholders the whole way • You hold a relevant degree; an advanced degree in CS, ML, Statistics, or a related field is a plus • You're comfortable in front of customers and executives, translating technical tradeoffs into business terms You're probably not a fit if… • You want to execute against someone else's architecture, not design your own • You'd rather avoid customer or stakeholder conversations than lead them • You think about the technology and skip the business context it lives in • You need long runway before shipping — this role moves fast and mixes design with execution • You want a playbook handed to you rather than writing the first one What Success Looks Like Your first 90 days goals: • Day 30 — You understand the AI architecture of the platform end to end — the systems, the constraints, the decisions already made. • Day 60 — You've shipped LLM-driven improvements and optimized existing flows for latency and reliability. • Day 90 — You own AI design across the platform — teams come to you before they build, not after. Compensation & Benefits • Competitive salary aligned with industry standards • Meaningful equity in a high-growth compliance AI company • Direct access to leadership — no bureaucracy between you and impact • Flexible, output-first culture — we care what you ship, not when you log on • Work on problems that matter in an industry that’s ready to change How to Apply & Important Notice Do you think that this is for you? apply directly or send your resume to [email protected]. Equal Opportunity Employment Sedric.Ai is an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, disability, or protected veteran status. AI & Recording Disclosure: To streamline our hiring process and ensure a thorough review, Sedric.Ai utilizes AI-powered tools to evaluate resumes, and our interviews may be recorded or assisted by an AI note-taker. By submitting your application, you acknowledge and consent to the use of these technologies during the recruitment process. If you prefer to opt out of AI resume screening or interview recordings, please notify our recruiting team at [Insert Contact Email/Link] to request a manual review or unrecorded interview.

We're looking for someone with a strong software engineering background and real hands-on AI experience- a leader who can think strategically, but is still comfortable diving into architecture, reviewing code, and solving complex technical challenges alongside the team. This role combines two key missions: enabling business units across the organization to develop AI solutions independently within secure and governed environments, while also building complex AI solutions for strategic business needs. Responsibilities Lead the development of secure, governed AI environments, including CI/CD security gates, LLM Gateway, Paved Roads, and approved development templates. Provide hands-on technical leadership for the AI development team, including architecture, code reviews, and complex problem-solving. Own project intake, risk classification, data governance, and controlled access to databases and data repositories, including Vector Databases for RAG. Work closely with the organization's Azure architecture, Information Security, Compliance, and business units. Build and lead the team, establish engineering standards, and support professional development. Requirements B.Sc. or higher in Computer Science, Software Engineering, Information Systems Engineering, or a related technological field. 6+ years of software engineering experience, including significant hands-on AI/LLM development and architecture experience. Hands-on experience with LLM APIs, RAG, Prompt Engineering, AI Agents, and tools such as Azure OpenAI, Claude, or equivalent technologies. Experience with CI/CD infrastructure and enterprise cloud environments. Practical knowledge of SQL/NoSQL databases, data governance, and controlled data access. Previous experience managing or leading an engineering team. Strong system-level thinking and the ability to bridge technical and business perspectives, while balancing innovation with security, governance, and regulatory requirements. Nice to Have Experience building an Internal Developer Platform. Familiarity with Vector Databases, Embeddings, and Agentic AI Workflows. Experience working in an enterprise organization with regulatory requirements and multiple business units. Relevant Azure certifications.

We’re looking for a hands-on AI Platform Engineer to join our team and help build an AI-powered R&D platform that transforms how engineering teams work throughout the software development lifecycle. You’ll design and develop production-grade AI Agents, from developer copilots to autonomous agents that can independently execute tasks and integrate directly into engineering workflows. This is a hands-on engineering role focused on building reliable, scalable AI systems that work in real production environments. Responsibilities Design, develop, and deploy AI Agents in production environments. Build end-to-end agent workflows integrated with CI/CD pipelines, code repositories, monitoring, and ticketing systems. Develop RAG pipelines using embeddings, retrieval techniques, and vector databases. Build tool-based agents that interact with APIs, services, and engineering tools. Implement agent orchestration, memory, state management, and human-in-the-loop workflows. Ensure system reliability through error handling, retries, and edge-case management. Optimize performance, latency, scalability, cost, and observability. Collaborate closely with engineering teams to integrate AI capabilities into daily development workflows. Requirements 2-5+ years of hands-on Backend or Platform development experience. Proven experience building and deploying LLM-based AI Agents in production. Hands-on experience with Claude and Claude Code- Mandatory. Hands-on experience with LangChain, LangGraph, or similar agent frameworks. Experience with LLM APIs, including OpenAI and Anthropic. Strong knowledge of RAG, embeddings, vector databases, and retrieval pipelines. Experience developing tool-based agents integrated with APIs and automated workflows. Experience with observability tools such as Langfuse or similar. Strong programming skills in Python or TypeScript. Nice to Have Experience with Multi-Agent or Autonomous AI Systems. Familiarity with DevOps, CI/CD, QA automation, or Developer Experience (DevEx). Experience with event-driven architectures, Kafka, or message queues. Experience integrating AI into code reviews, automated testing, or incident analysis. Why Join Us? Join a team building AI systems that directly impact how developers work. You’ll have the opportunity to take ownership of complex AI solutions, from architecture and development to production deployment, while working with cutting-edge technologies in Agentic AI.

Description About Slice Global Equity Slice Global Equity is redefining how companies manage equity, compliance, and tax across borders. We've raised $32M to date, including a Series A led by Insight Partners, with continued backing from TLV Partners, R-Squared Ventures, and Jibe Ventures. Slice is building an AI-native equity platform that automates global compliance in real time, across 60+ countries. We sit at the intersection of fintech, legaltech, and AI, solving one of the hardest infrastructure problems in global business. We're headquartered in New York City, with an office in Tel Aviv. We move fast, take ownership, and think AI-first. If that sounds like you, we'd love to meet you. The Role We are looking for a Strong AI Backend Engineer to join our core R&D team and build the next generation of AI-powered features that simplify global equity management. You’ll design, build and deploy systems and AI agents that extract, understand, and act on complex financial and legal data - in real time. Your work will directly power customer-facing AI interfaces, advanced document automation, and real-time compliance decision engines across the Slice platform. Key Responsibilities • AI & Agent Development: Design, Deploy and Evaluate sophisticated AI agents and workflows integrated directly into Slice’s core SaaS infrastructure. • End-to-End System Engineering: Design, build, and maintain robust backend systems and data pipelines, taking features from initial concept all the way to production. • Core Vertical Impact: Contribute to and drive features across our primary AI focuses, including Document Automation, Customer-Facing Agents, real-time decision engines. • Production Optimization: Continuously evaluate and fine-tune system and model performance for accuracy, latency, scalability, and cost. • Cross-Functional Collaboration: Partner directly with the CTO, platform engineers, product, and design teams to deliver user-facing AI capabilities. • Stay current with advances in LLMs, text analysis, and generative AI to guide product innovation. Requirements Required Qualifications • Core Backend Development: 6+ years of experience in backend engineering (with strong proficiency in Python). • Applied AI Experience: 2+ years of hands-on experience as an AI Engineer, with a proven track record of deploying practical AI/ML systems into real-world production environments. • Agentic Frameworks: Solid experience building and integrating AI agents and workflows using frameworks like LangGraph, LangChain, PydanticAI etc. • Product Ownership: Ability to take projects end-to-end from research to production rollout, while translating product requirements into production-ready engineering solutions. • Communication: Excellent written and spoken English, with strong collaboration skills. Nice to Have • NLP & Text Processing: Familiarity with NLP/ LLM architectures, and text-extraction or document-processing pipelines. • Experience with vector databases or RAG pipelines. • Familiarity with compliance, fintech, or document-intensive domains. • Experience in cloud-based ML deployment (GCP preferred). Why Join Slice • Build with purpose: Apply AI to solve global compliance at scale. • High ownership: Work directly on product-critical systems with real customer impact. • Technical depth: Work across architecture, UX, and infrastructure. • Collaboration: Partner with top engineers and designers in Tel Aviv. • Team culture: Collaborative, ambitious, and impact-driven. • Startup energy: Join a high-growth company backed by top investors, scaling globally, and redefining fintech infrastructure.

We are making the future of Mobility come to life starting today. At Autofleet we support the world's largest vehicle fleet operators and transportation providers to optimize existing operations and seamlessly launch new, dynamic business models - driving efficient operations and maximizing utilization. We are looking for a talented AI Engineer to help us develop advanced AI solutions that will empower impactful projects. The Data Science team leads the AI research and innovation efforts of the company, and is focused on pushing AI boundaries to enhance the product and optimize processes. What You’ll Do • Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions • Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails and audit trails. • Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback. • Implement integrations that allow agents to take automated actions on behalf of users, streamlining workflows and reducing overhead. • Collaborate with engineering teams to design, build, and maintain production pipelines. Requirements • Bachelor’s degree in Computer Science, Engineering, Mathematics, Physics, or a related quantitative discipline. • 5+ years of software engineering experience, with proven ability to build production-grade systems beyond research, experimentation, or prompt engineering. • Hands-on experience building and operating production-grade AI/LLM systems, ideally including agentic workflows, tool-calling, orchestration, evaluations, or multi-step reasoning systems. • Strong backend expertise, including Python, distributed systems, and cloud-native architecture. • Familiarity with the AI Agents ecosystem, including different LLM providers, vector store solutions, MCPs, A2A and more. • Familiarity with REST APIs and integrating external data sources.

The Mission Cybersecurity moves at the speed of code, but security management still moves at the speed of humans. Critical insights are often trapped in siloed scan results, complex attack paths, or the tribal knowledge of senior researchers. These processes don’t scale, they can’t be automated, and they leave organizations vulnerable in the gaps between tools. CYE’s AI & Innovation team is changing that. You’ll build production-grade AI agents and modular AI capabilities that live atop the Cye Platform. You aren’t just building features; you are building an AI-native operating system for cyber risk. Every complex security workflow—from data acquisition to autonomous mitigation—will become legible to code, runnable by anyone, and composable into larger defense strategies. Who We Are 🛡️ The Product: CYE is the leader in data-driven cyber risk management. The Cye Platform uses advanced mathematical models and world-class security research to help organizations move from reactive patching to proactive risk orchestration. 🚀 The AI & Innovation Team: We are the architects of CYE’s intelligence layer. Our team is composed of security researchers and engineers who treat LLMs as a new reasoning primitive for cybersecurity. We are responsible for the core AI infrastructure and agentic workflows that allow the CYE Platform to think, prioritize, and act at scale. 📈 Momentum: Backed by global powerhouses like EQT, CYE secures many of the world’s most complex enterprises. As the threat landscape evolves through AI, our team ensures that the defense stays ahead. About the Role In this role, you will: • Build Modular AI Capabilities: Design and implement self-contained "AI Skills" that connect to the CYE Platform’s core data layers. • Ship End-to-End Autonomous Agents: Build agents that don't just "think," but act. You will deploy agents that handle the heavy lifting of the security lifecycle. • Bridge the Gap to Non-Technical Users: Create the abstractions that allow our customer success teams and client stakeholders to trigger or chain these AI workflows. • Own the AI Infrastructure & Evaluation: Maintain and contribute to the environment where these agents are born, ensuring they are grounded in truth. About You • You build for production, not for Twitter: You’ve built AI agents that operate autonomously in the real world. You understand how to handle edge cases and ensure reliable, structured outputs. • Strong Product Instincts: You have a natural intuition for user experience and a "force multiplier" mindset. You identify which manual security workflows are ripe for disruption and enjoy turning them into clean, automated code. • You code at the speed of thought: You are a power user of AI-assisted coding tools (like Claude Code, Cursor, or similar) and modern LLM APIs. • You think in systems: You enjoy the challenge of connecting disparate stages—acquisition, reasoning, and mobilization—into a single, cohesive intelligence layer. Requirements • Professional Experience: 3+ years of experience in dedicated AI development (LLMs, agentic workflows, RAG). • Senior Engineering Track: Alternatively, we value 7+ years of Senior Software Engineering experience combined with at least 1 year of deep AI development. • Education: A Bachelor’s or Master’s degree in Computer Science or Electrical Engineering is a major bonus. • Technical Mastery: Deep proficiency in Python and the modern AI stack, with the ability to architect systems that require high reliability. You’re Not a Fit If You… • Aren't a practitioner of AI-assisted coding. We live in Cursor and Claude Code; it is core to our DNA. • Prefer building in a vacuum. This role requires deep empathy for our security researchers and the collaborative process of translating expertise into code. • Are looking for a "Research" role. We value agents that work reliably in production over theoretical models in a notebook. Why You'll Love It ❤️ The People & Culture: At CYE, we believe our greatest asset is our DNA. We have built a culture where people are empowered to take ownership and where genuine relationships are the key to our success. 🛡️ High Stakes, High Impact: You are building the automated defense systems that protect some of the world's most critical organizations. 🚀 Autonomy and Agency: We hire experts and stay out of their way. You’ll have the agency to define how these agents are built and deployed. 🛠️ An AI-First Environment: From our development workflows to our core product architecture, you will be in an environment that truly embraces the "speed of AI." Ready to build the future of autonomous cybersecurity? We’d love to hear from you. Cye helps security and risk leaders gain a clear, defensible view of their cyber exposure, grounded in financial impact and real-world attack paths. By continuously quantifying exposure and validating it in context, organizations can establish a strong baseline, prioritize decisions with confidence, and track measurable reduction over time.

Your work days are brighter here. We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too. About the Team At Paradox, we believe when you get the people thing right, you can build teams that change the world. As part of Workday, we are laser-focused on building world-class products—backed by a decade of leadership in Conversational AI. Our Tel-Aviv R&D center is where deep experience meets next-generation technology. We aren't just experimenting with Large Language Models, we are deploying them at an unmatched global scale. We combine our historical data advantage with advanced LLM capabilities to directly influence the hiring experiences of millions of candidates worldwide. Sound like your perfect fit? We want to hear from you! About the Role As a Senior Applied AI Engineer, you will lead the bridge between cutting-edge AI capabilities and production-grade software. You will design, build, and optimize the intelligent systems, agentic workflows, and LLM-driven architectures that power Paradox’s conversational products. Also, you will combine software engineering rigour with state-of-the-art Generative AI techniques - optimizing for conversational quality metrics, latency, and system reliability in high-scale production environments, serving millions of users. We are looking for an engineer who is hungry for AI innovation, eager to pioneer new generative capabilities, and passionate about shipping impactful AI solutions. In this role, you will: • Design & Scale AI Systems: Architect and deploy high-performance LLM orchestration systems, agentic workflows, retrieval-augmented generation (RAG) pipelines, and AI microservices. • Bridge AI Research & Production: Transform frontier LLM research, foundation models, and generative techniques into robust, production-ready features with high availability and low latency. • LLM Evaluation & Guardrails: Design and implement automated LLM evaluation (evals) frameworks, benchmark suites, and guardrail policies to continuously measure accuracy, reduce hallucinations, and ensure safety across product flows. • Optimize Performance & Cost: Lead latency, throughput, and token-cost optimization strategies across commercial APIs and open-source models. • Set AI Engineering Standards: Elevate software craftsmanship across the team through architectural reviews, code quality, and LLMOps best practices, utilizing the latest AI tools. • Drive Product Innovation: Collaborate closely with product and engineering teams to translate complex human resource and conversational challenges into intelligent software solutions. About You Basic Qualifications: • Applied Generative AI: Proven track record of shipping complex LLM systems to production (e.g., Multi-agent architectures, RAG systems, tool/function calling, complex dialogue managers) coupled with a passion for continuous AI innovation. • 5+ years of hands-on software development experience, focusing on building complex, distributed systems. • System Architecture & Cloud: Strong system design skills in cloud-native environments (AWS/GCP), containerization, and modern CI/CD automation. • Engineering Quality for AI: Deep understanding of testing non-deterministic AI systems (eval-driven development, deterministic regression testing, automated benchmarking). • Technical Leadership: Proven experience leading architectural designs, driving cross-functional alignment, and mentoring engineers in AI engineering principles. • Fluent English: High proficiency in both written and verbal communication. • Work Authorization: Authorization to work in Israel. Preferred Qualifications: • Python Expertise: Deep proficiency in Python and modern backend framework development, with strong API design and asynchronous programming skills. • Vector Search & AI Infrastructure: Hands-on experience with Vector Databases (e.g., Pinecone, Qdrant, Milvus, pgvector) and modern orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen/CrewAI). • Model Customization & Fine-Tuning: Practical experience with model fine-tuning techniques (e.g., LoRA, QLoRA, SFT, DPO/RLHF) and dataset curation. • LLMOps & Observability: Hands-on experience with LLM tracing and observability stacks (e.g., LangSmith, Phoenix, Arize, Weights & Biases). • Inference & Serving: Familiarity with LLM serving engines and frameworks (e.g., vLLM, TensorRT-LLM, Ollama). • Domain Experience: Background in Conversational AI, Dialogue Management, or Recruitment/HR tech automation. • Data Science/ML Foundation: Formal background or practical grounding in NLP, Machine Learning, or Data Engineering. Our Approach to Flexible Work With Hybrid Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so we require employees to work three days a week in the office and two days at home. This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law. Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law. If you require a reasonable accommodation, you may email [email protected], as far in advance as possible. Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process! At Workday, we value our candidates’ privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not. In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.

Description Mentee Robotics, now part of Mobileye, brings world-class robotics expertise, together with Mobileye's decades of leadership in computer vision, machine learning, and autonomous driving technologies. Building on that foundation, Mentee by Mobileye is creating the "MenteeBot", the AI-first humanoid robot that combines perception, reasoning, learning, and advanced dexterous manipulation, designed to work alongside people in their everyday lives, at the workplace and in the home. At Mobileye, our technologies power more than 230 million vehicles worldwide and have helped shape the future of autonomous mobility. With teams around the world, we continue to innovate at the forefront of autonomous systems, advancing the next generation of Physical AI for real life. Responsibilities You will build agentic systems for robotics: LLM- and VLM-based agents that plan tasks, call robot skills as tools, verify outcomes and recover from failure, along with the harnesses that evaluate them in simulation and on the robot. You will develop advanced data-generation methods for deep learning models, combining 3D simulation, reinforcement learning and spatial agents to produce realistic, diverse training data at scale. You will reconstruct real environments and objects with Gaussian splatting and 3D computer vision, and bring them into simulation with correct geometry, so our models train where they will be deployed. You will take this work from prototype to production-grade pipelines on distributed GPU compute. Requirements • B.Sc. in Computer Science, Engineering, or a related field. • 4+ years of hands-on experience in machine learning, computer vision, or robotics software engineering. • Python Expertise: Extensive experience and strong proficiency in Python, a must-have. • Deep learning: Proven experience building and scaling deep learning pipelines (PyTorch), beyond just using existing ones. • Breadth: Hands-on experience in at least one of agentic LLM/VLM systems, simulation/RL data generation, or 3D reconstruction, and familiarity with the others. Advantages • M.Sc. or Ph.D. in Computer Science, Robotics, Computer Vision, or a related field. • Experience with robotics simulators (e.g. Isaac Sim / Isaac Lab, MuJoCo), reinforcement learning, or sim-to-real transfer. • Experience with Gaussian splatting / NeRF, SfM/SLAM (e.g. COLMAP), or meshes for simulation. • Experience applying foundation models to robotics: VLM planners or verifiers, VLA models, open-vocabulary perception. • Comfortable working in cloud and distributed environments (e.g. AWS, SLURM) and with ROS 2 on real robotic platforms.

Description About AllCloud AllCloud is a leader in amplifying organizations’ cloud potential through AI. With a track record of hundreds of successful migrations and implementations across AWS and Salesforce, AllCloud has developed strategies and solutions that enable businesses of all sizes to remain at the forefront of innovation. AllCloud is a leader in AI-led professional and managed services. As an AWS Premier and audited managed services Partner, and Salesforce Consulting partner, AllCloud provides comprehensive AI-led cloud journey support, from initial migration to ongoing management through our Engage Managed Services. Our expertise ensures that clients remain aligned with ecosystem best practices while focusing on their core business growth. AllCloud serves clients across the globe with offices in EMEA and North America. www.allcloud.io Job Summary We are seeking a highly skilled and motivated Senior Software Engineer GenAI to join our growing R&D team. In this role, you'll design, develop, and scale our next-generation backend platform, AI-driven workflows, and GenAI applications. You'll work with modern cloud technologies and LLMs to build resilient, high-performance systems while contributing to architecture, technical leadership, and mentoring. This role is ideal for an experienced backend engineer who enjoys solving complex technical challenges, building scalable systems, and working with cutting-edge AI technologies. Key Responsibilities • Design and develop scalable backend services using Python. • Build resilient distributed systems, microservices, and AI-driven workflows. • Integrate Large Language Models (LLMs) using AWS Bedrock and other AWS services. • Design and implement event-driven architectures and modern APIs. • Optimize databases, search capabilities, and caching strategies to support high-performance applications. • Contribute to cloud infrastructure, CI/CD pipelines, and observability practices. • Collaborate with Product, Data Science, and Engineering teams to deliver scalable solutions. • Provide technical leadership through architecture discussions, mentoring, and hands-on development. Requirements • 5+ years of backend software engineering experience. • Strong Python development skills, preferably with FastAPI and/or Django. • Experience designing scalable distributed systems and microservice architectures. • Experience building AI-powered applications or integrating LLMs (AWS Bedrock preferred). • Experience working with SQL and NoSQL databases, ORM frameworks, and query optimization. • Familiarity with event-driven architectures, messaging technologies (Kafka, Celery, or similar), and distributed caching (Redis). • Experience building REST, GraphQL, or gRPC APIs using Nest.JS or FastAPI or Django and LiteStar. • Experience with Docker, CI/CD pipelines, Infrastructure as Code (IaC), and cloud-native development. • Knowledge of monitoring and observability tools such as OpenTelemetry, Prometheus, Grafana, Datadog, or similar. Nice-to-Have Skills • Experience with Retrieval-Augmented Generation (RAG) or vector search technologies. • Experience with OpenSearch or graph databases such as Neo4J / Neptune. • Frontend experience with React or Angular. • Experience working in enterprise or highly regulated environments. Why work for us? Our team inspires progress in each other and in our customers through our relentless pursuit of excellence. You'll work alongside experienced technical leaders who encourage innovation, continuous learning, and professional growth. We offer competitive salaries, bonus incentives, comprehensive benefits, flexible working hours, and the opportunity to build cutting-edge AI solutions on AWS. Apply now to become part of the team. AllCloud is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis protected under applicable law.

Description About AllCloud AllCloud is a leader in amplifying organizations’ cloud potential through AI. With a track record of hundreds of successful migrations and implementations across AWS and Salesforce, AllCloud has developed strategies and solutions that enable businesses of all sizes to remain at the forefront of innovation. AllCloud is a leader in AI-led professional and managed services. As an AWS Premier and audited managed services Partner, and Salesforce Consulting partner, AllCloud provides comprehensive AI-led cloud journey support, from initial migration to ongoing management through our Engage Managed Services. Our expertise ensures that clients remain aligned with ecosystem best practices while focusing on their core business growth. AllCloud serves clients across the globe with offices in EMEA and North America. www.allcloud.io Job Summary AllCloud is seeking a Senior Generative AI Engineer to lead the design, development, and deployment of cutting-edge Gen AI solutions. This role is ideal for experienced AI professionals with a strong technical background, a track record of delivering scalable AI systems, and the ability to mentor and guide team members. The Senior Engineer will drive end-to-end AI projects, architect reliable AI platforms, and collaborate closely with product, engineering, and business teams to deliver high-impact solutions. Summary of Key Responsibilities • Lead the design and implementation of Gen AI platform components using Python and modern microservices. • Drive engineering and operational best practices across AI projects. • Collaborate with technical, product, and business teams to deliver customer value and define product vision. • Lead end-to-end development of AI systems, including research, experimentation, deployment, and scaling. • Mentor and support engineers, fostering collaboration, knowledge-sharing, and continuous learning. • Analyze complex problems, define requirements, and propose AI-driven solutions. • Apply DevOps principles to maintain secure, scalable, and high-performance AI systems. • Design and implement secure APIs for safe interaction with AI models. • Stay up-to-date with the latest Gen AI technologies and trends, and bring innovation to the team. Requirements • 5+ years of experience in AI, ML, or software engineering, with at least 2 years focused on Generative AI. • Strong understanding of LLMs, RAG techniques, fine-tuning, inference, and Gen AI workflows. • Expertise in Python and relevant Gen AI libraries and frameworks (PyTorch, TensorFlow, HuggingFace). • Experience designing, deploying, and scaling AI platforms and microservices. • Familiarity with vector databases (OpenSearch, Pinecone, FAISS) for data storage and retrieval. • Excellent problem-solving, analytical, and leadership skills. • Strong interpersonal, team, and communication skills. • Academic degree in Computer Science, AI, Data Science, or equivalent; advanced degree preferred. Certifications • AWS Machine Learning Specialty (Strongly Preferred) • AWS Solutions Architect – Associate (Strongly Preferred) • AWS Solutions Architect – Professional (Preferred) Why Work for Us? At AllCloud, you will lead the development of next-generation AI solutions and mentor a high-performing engineering team. We offer competitive salaries, flexible working hours, mentorship, benefits, and opportunities to influence product vision and Gen AI innovation. AllCloud is an Equal Opportunity Employer and considers applicants for employment regardless of race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, provincial, or local law.

Description If you've ever dreamt of being there when it all started, this one's for you. At Zeroport, we're rethinking how humans and AI agents securely access and interact with critical systems. As AI becomes more autonomous, controlling what it can access is no longer enough. We're pioneering Least Agency: limiting what AI agents (and humans) can actually do, and enforcing those boundaries independently through physical containment. Our approach combines purpose-built hardware, robust software, and non-IP connectivity to enable secure, real-time work for both AI agents and humans, without exposing the protected network. It sounds bold, we know. That's exactly the point. Who We Are Zeroport is pioneering Least Agency for AI and human network access. Our hardware-enforced architecture creates physical boundaries between AI agents, human users, and critical systems, limiting what they can reach and do by design. We're a focused, technical team with a strong builder mentality, moving fast to redefine how humans and AI securely interact with the world's most critical systems. About the Role We're hiring a senior AI Engineer to join our AI team building our autonomous AI agent and helping extend AI capabilities across the company. The agent runs on NVIDIA hardware integrated inside our purpose-built platform, watches up to 200 concurrent video streams from our hardware-isolated remote access solution, and is the only path to compliance and threat detection in an environment that intentionally blocks every traditional monitoring channel. Larger deployments span multiple edge units coordinating across sites, and the whole system ships into fully air-gapped customer networks — updating, learning, and evolving without ever touching the cloud. This is not a wrap-a-model-in-an-API role. You'll work on real production-grade agent systems, deep multimodal inference at the edge, and the infrastructure that makes both ship and scale. What You'll Do • Design and ship our agent systems end-to-end — perception, reasoning, memory, retrieval, and the loops that connect them. Production agents, not prototypes. • Optimize multimodal inference for real-time operation at the edge — model choice, quantization, and batching to hit our latency and concurrency budgets. • Design embedding pipelines, vector storage, and hybrid retrieval that power the agent's search, behavioral analytics, and rule generation. • Architect how multiple edge units coordinate at scale — sharing context, correlating activity, and behaving as one coherent system for our largest deployments. • Build the agent's air-gapped lifecycle — updating, learning, and evolving entirely inside customer private networks with no cloud connectivity. • Run focused research on new open-source models and inference frameworks, and bring back insights and prototypes that inform our roadmap. Plus occasional cross-company AI projects across the rest of the company. Requirements Who You Are We care about a particular mindset more than any specific item on a checklist. The person who'll thrive here is someone already living inside the modern AI stack - not planning to start. You read model release notes the way other people read the news. You've built real things with new tools the week they came out. Agentic dev workflows aren't something you've heard about; they're how you already work. When a new model drops, your first instinct is to put it on the bench. And underneath all of it, you're a builder - you ship, you write clean software, and you think about latency, cost, and what the user actually needs. What We're Looking For • 6+ years of software engineering experience, with the last few focused on AI / ML systems • Deep, hands-on experience designing and shipping agent systems in production - not demos. You understand agent architectures, memory, tool use, evaluation, and the failure modes that matter at scale. • Strong fundamentals in embeddings, RAG, and hybrid retrieval, with real experience designing vector storage and retrieval pipelines for production use • Deep production backend foundations - strong Postgres knowledge (functions, triggers, indexes, extensions, atomic operations, and similar depth), real-time client channels (WebSockets, SSE), async and event-driven backbones (pub/sub, queues, background tasks, webhooks), the ability to design systems and features around multithreading and multiprocessing, and dynamic resource management for high-throughput, latency-sensitive workloads. • Excellent architecture instincts and strong Python - you write code that scales and that other engineers can build on • Product sensibility - you can reason about trade-offs and what's worth building, not just what's technically possible Nice to Have • Experience with vision-language models and multimodal systems • Experience running AI workloads on edge hardware (Jetson, NVIDIA accelerators, custom inference rigs) • Familiarity with vLLM, TensorRT, or similar inference stacks; quantization and model optimization • Experience with video streaming technologies (WebRTC, GStreamer, STUN/TURN) • Background in networking, cybersecurity, or systems-level Linux • Experience with model fine-tuning and dataset construction Why Join Us • Be part of designing innovative solutions for some of the toughest challenges in network security • Flexible work setup, minimal bureaucracy • Real ownership and impact from day one • A collaborative and innovative work culture • Competitive salary and benefits Let's build it together! Even if you don’t meet every requirement – we’d still love to hear from curious, motivated people.

Description Alice's RL Environments team builds adversarial environments that the world's leading AI labs use to test and train their most capable agents. Each environment is a working replica of a real system with an attack planted inside it. A verifier decides whether the agent held up. The environments run on AgenticVerse, our platform for building and running RL environments at scale. A large and fast-growing community of researchers works on it every day. We're looking for a Senior AI Engineer to own those environments and the evaluation that decides which tasks are good enough to train a frontier model. What you'll do RL environments • Build RL environments end to end: the replica systems, the planted attack, and the verifier that grades the run • Own environment and verifier design for tool-use, web, and computer-use agents • Make environments airtight: sandboxed, free of eval-awareness cues, and closed to reward hacking • Read rollout traces, find where the agent took a shortcut, and close it Task evaluation • Own Alice's proprietary task evaluator, the engine that decides whether a task is ready for a frontier lab • Make it the industry's sharpest quality bar for RL tasks: realism, threat-model accuracy, and training value • Keep it learning: every customer review and every post-training run makes it stricter Run infrastructure • Scale the run pipeline: queue-driven runners on Kubernetes, per-run sandboxes, and a grader the agent can't reach • Package environments so they drop into customer training and evaluation pipelines Working with Research • Work with researchers as one team, from a task idea to an environment that's ready to train on • Turn what post-training runs reveal into fixes in the environments • Review designs and code, and raise the engineering bar for the people around you Requirements What we're looking for • 6+ years as a backend engineer, building production systems • BSc in Computer Science or a related field, preferably from a leading university • Strong Python, and production experience with Docker, Kubernetes, and cloud infrastructure (AWS preferred) • Experience designing distributed systems and message queues • A track record of owning systems from design to production • High autonomy in an undefined space. You take a loose problem and come back with working code • Fluent written and spoken English Advantage • Academic background in AI or machine learning: a degree, thesis, or research • Hands-on AI engineering: building with LLMs, agents, or evaluations • Exposure to post-training: RL fine-tuning, reward design, or rollout analysis • Background in security, red teaming, or trust and safety About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Description Alice is a leading platform for Trust & Safety teams worldwide, leveraging cutting‑edge AI and world‑class expertise to protect users from the widest spectrum of online harms. By continuously collecting and analyzing data, our solutions ensure customers stay two steps ahead of bad actors in an ever‑changing threat landscape. We’re seeking an outstanding Backend Engineer with a Generative AI orientation to join our research team. We are building a new AI Platform from scratch to standardize AI development methods, ensure excellence and efficiency, and deliver robust, scalable, and compliant AI capabilities. This platform will handle GenAI models deployment, prompt management, data filtering, logging, and monitoring, centrally, so individuals can focus on their own business-specific logic. Key Responsibilities • Build and maintain CI/CD pipelines that support fast, reliable integration and deployment of GenAI systems across complex environments, including orchestrating multiple models/agents and MCP clients/servers. • Develop, deploy and integrate AI solutions and agentic frameworks, creating both command‑line tools and interactive notebooks that support our team’s research and workflow automation needs. • Build and manage data pipelines and databases (SQL) for large‑scale data handling, automating data collection and curation (e.g., adversarial prompts for model red-teaming) to support AI training and evaluation. • Integrate research into production by implementing the latest generative AI advancements (including white‑box LLM development), integrating different models and agents, and developing evaluation frameworks (e.g., agentic reasoning tests) as part of our automated workflows. • Integration & Orchestration: Integrate dockerized environments (e.g., Harbor format) into internal training frameworks, optimizing reset/statefulness semantics, concurrency, and throughput ceilings • Deploy GenAI models from repositories such as HuggingFace onto our AWS platform, connect them to data pipelines, and automate end‑to‑end processes for prompt generation, labeling, and response evaluation. Requirements Must-to-have • B.Sc. in Computer Science, Computer Engineering, or a related field (or equivalent hands‑on experience). • 5+ years of experience delivering large‑scale, high‑performance systems on AWS, with an emphasis on orchestrating data pipelines and AI workflows in production environments. • Expertise in scripting and automation using Python and shell; proven ability to write clean IaC and CI/CD pipelines. • Strong understanding of Linux systems, networking, and distributed system design. • Ability to break down monolithic systems into scalable, loosely coupled services and microservices. • Strong cross‑functional communication and collaboration skills, with a DevOps mindset to drive best practices across teams. • Hands‑on experience deploying and integrating generative AI models (e.g., large language models or other AI/ML models) in production. • Hands‑on experience deploying MCP clients/servers and integrating them into automated AI workflows. Nice-to-Have • M.Sc. in Computer Science, Computer Engineering, or a related field. • Experience with large‑scale cluster management or HPC scheduling tools (e.g., Slurm). • Knowledge of advanced observability and monitoring tools such as Prometheus and Grafana. • Experience with cloud cost optimization (FinOps concepts) and exposure to infrastructure security tools or configuration management for compliance. • Hands‑on experience working with A2A protocol. Alice is the leading provider of security and safety solutions for online experiences, safeguarding more than 3 billion users, top foundation models, and the world’s largest enterprises and tech platforms every day. As a trusted ally to major technology firms and Fortune 500 brands that build user-generated and GenAI products, Alice empowers security, AI, and policy teams with low-latency Real-Time Guardrails and a continuous Red Teaming program that pressure-tests systems with adversarial prompts and emerging threat techniques. Powered by deep threat intelligence, unmatched harmful-content detection, and coverage of 117+ languages, Alice enables organizations to deliver engaging and trustworthy experiences at global scale while operating safely and responsibly across all threat landscapes. About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Description About Immunai: Immunai is an AI-driven platform company focused on improving drug discovery and development by decoding the human immune system. We combine large-scale single cell immune data, advanced machine learning, and strong engineering to help pharmaceutical and research partners make better, more informed decisions throughout the drug development process. Our long-term goal is to reduce drug development failure rates and help more effective medicines reach patients. We’re building this platform thoughtfully and collaboratively, bringing together expertise across biology, AI, engineering, and business. Immunai is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. About the role: We are looking for an ML Infra Engineer to play a central role in evaluating, and deploying Immunai’s AI models. You will own and evolve Immunai’s benchmarking and evaluation capabilities for foundation models and multimodal systems, while also working closely with modeling teams to support model development, iteration, and validation. This role sits at the intersection of software engineering, model understanding, and applied AI, with broad influence on how models are built, compared, and improved across the organization. This is NOT a core algorithmic research role - but rather, a role focused on building out the ML engineering infrastructure for the evaluation and deployment of models. Location: Ramat Gan, Israel (hybrid model) What will you do? • Own & Evolve Benchmarking – Design, build, and maintain Immunai’s benchmarking suite for foundation models and multimodal AI systems. • Define Core Abstractions – Create clean, extensible abstractions and APIs for datasets, tasks, models, metrics, and evaluation workflows. • Develop Metrics & Evaluations – Implement metrics that capture predictive performance, biological relevance, and multimodal alignment. • Support Model Development – Work closely with AI scientists and data scientists to integrate new models, tweak architectures, and enable rapid, fair iteration. • Bring in New Models & Baselines – Add external and internal models to benchmarks and ensure meaningful comparisons. • Explore Data When Needed – Dive into data and results to debug evaluations, understand model behavior, and unblock modeling work. • Enable Rigor & Reproducibility – Ensure evaluations are consistent, well-versioned, and trustworthy over time. Requirements Required qualifications: • BSc, MSc, or PhD in Computer Science, Software Engineering, or a related field • Strong software engineering skills with experience designing maintainable, modular systems • 5+ years hands-on, industry experience working with ML models and evaluation pipelines - a must • Proficiency in Python and modern ML ecosystems • Ability to read, modify, and debug deep learning models • Experience with benchmarks, metrics, or evaluation frameworks — preferred • Familiarity with foundation models or multimodal learning — preferred • Comfort navigating complex datasets and doing targeted exploratory analysis • Experience in biomedical or other data-intensive domains — a plus Desired personal traits: • You want to make an impact on humankind • You prioritize “We” over “I” • You enjoy getting things done and striving for excellence • You collaborate effectively with people of diverse backgrounds and cultures • You have a growth mindset • You are candid, authentic, and transparent When you apply for a role at Immunai, we process your personal data (such as CV, contact details, and professional background) to assess your suitability for current and future roles. Your information may be shared internally with relevant employees and stored or processed by trusted service providers, some of whom may be located outside your country of residence. You can read more about how we process data here: https://www.immunai.com/privacy-policy/.

We're looking for a Founding AI Engineer to build and define the research function at Upriver from zero. This is a rare opportunity to work on some of the hardest unsolved problems in applied AI and agents, with massive ownership, visibility, and room to grow into leadership quickly. What You'll Do Lead the AI domain at Upriver: Take ownership of our agent architecture and help define its next phases, standards, and direction. Solve hard, unsolved problems: Work on challenges in AI agents, reasoning over complex systems, and autonomous decision-making that don't yet have clear playbooks. Build production AI: Design, implement, evaluate, and deploy AI systems used by real customers. Be outward-facing: Publish technical blogs, benchmarks, and papers; represent Upriver in the AI and data community. Move fast with autonomy: Own problems end-to-end with minimal guidance, working directly with founders. Deliver real customer value end-to-end: take features from idea to production, see them used by customers, and iterate based on real-world impact. What We're Looking For Strong background in AI / ML (applied research, systems, or both). Experience building or experimenting with hands-on software development. Comfortable operating independently and making foundational technical decisions. Strong communication skills and interest in writing, publishing, and sharing work publicly. High ambition and desire to grow into a technical leadership role. Extra: Hands-on experience experimenting with large language models (LLMs). Why Upriver Define a new category: Be part of a team figuring out how AI agents actually work inside real data platforms, and build a category leader product. High ownership, high trust: You'll make real architectural and product decisions early on. Top-tier team: Work with exceptional engineers at a very high bar. Join at the inflection point: Strong early traction, a fresh seed round, and the opportunity to grow rapidly with the company as it scales.

LEDGE'S MISSION is to reinvent how finance teams work by building AI agents that actually do the work, not just automate it. We began with an industry-leading reconciliation platform used by top finance teams. We are now broadening our scope to develop a completely AI-native close management solution, built upon our strong existing platform that is already competitive with leading industry offerings. Our agents autonomously prepare, reconcile, validate, and manage the close end-to-end with finance-grade accuracy and transparency. We’re designing new tools for the Office of the CFO: a scalable, trustworthy data pipeline combined with autonomous AI workflows and a clean, consumer-grade experience. As an AI-first engineering organization, we use modern microservices, full IaC, and advanced AI coding and development tooling to move fast and build real autonomy into the finance workflow. ‍ The role AI Engineers at Ledge take true end-to-end ownership from scoping agent behaviors and designing model-driven architectures to deploying and monitoring production AI systems. You’ll help evolve our reconciliation engine and build the next generation of AI agents powering the automated financial close, solving deep technical, data, and product challenges in partnership with accounting and finance experts. ‍ What we are looking for • Experience building or orchestrating AI agents • Background in model evaluation, prompt engineering, or autonomous workflow design • You thrive in a fast-paced startup environment and are willing to work hard to achieve ambitious goals • You have a get-things-done attitude and deliver high-quality work quickly • You have 5+ years of software engineering experience, including building or integrating AI systems • You are a proactive team player motivated to impact the team, the product, and the customers • You have strong fundamentals in distributed systems, data flows, and cloud/web architectures • You are an independent, fast learner excited about mastering new AI technologies and tooling ‍ Nice to have • Experience with payments, accounting, or finance • Experience working on AI-first teams or with LLM-based systems • Experience developing high-performance, real-time, customer-facing applications • Experience with typescript and nodeJs

At Lightrun, we’re closing the gap between AI-generated code and real-world runtime behavior. Our platform restores the critical verification loop in enterprise environments by enabling safe, real-time observability - logs, metrics, and traces injected on demand into live systems - so engineers and AI agents can validate assumptions where code actually runs.Backed by Accel and Insight Partners, and trusted by leaders like Microsoft, Salesforce, Citi, and SAP, Lightrun is building the runtime foundation for the next era of agentic software development. Join us to build cutting-edge systems, collaborate with world-class engineers, and shape how autonomous software is built in production. We are looking for an AI Engineer to join the hunt. Responsibilities: • Take part in the design and development of AI-driven features for our Dev-Native Observability Platform. • Collaborate with cross-functional teams to integrate AI solutions into existing systems. • Contribute to the product roadmap by identifying AI opportunities and providing insights as a potential end user • Stay updated with the latest AI trends and technologies to ensure our platform remains cutting-edge. Requirements: • At least 3 years experience in Python / TS working with AI/ML frameworks • At least 5 years of backend experience with at least one additional programming language (Java / C# / Node.js / C++) • At least 3 years experience working with database solutions (RDBMS, NoSQL, Vector) • Proven experience with writing efficient and useful LLM prompts • Proven experience building LLM-based solutions and integrating them into products • Strong system and architecture design skills, particularly in designing LLM based systems • Experience or at least substantial knowledge of GenAI technologies such as agentic flows, RAG, model fine-tuning / distilling, prompt engineering, context engineering • Hands-on experience with cloud platforms and their AI/LLM services • Experience working on a SaaS product - Advantage • Experience working with customers and direct customers feedback - Advantage • Experience using observability / profiling / remote debugging tools - Advantage • Passionate about AI and up to date with industry trends - Advantage

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. Job Summary: Cymbio (Acquired by PayPal) is a leading orchestration platform that provides a seamless, one-to-many connection for merchants to be discoverable and purchasable across agentic commerce surfaces like Co-Pilot and Perplexity, as well as marketplaces and dropship retailers, including Nordstrom, Macy’s, and TikTok. Now a proud part of PayPal, we eliminate the need for complex point-to-point integrations and manual work, slashing time-to-live from months to days. Global brands like Balmain, New Balance, and Fabletics rely on Cymbio to automate and syndicate their product, inventory, and pricing feeds, while effortlessly orchestrating orders and returns across hundreds of surfaces globally. Job Description: Essential Responsibilities: • Delivers complete solutions spanning all phases of the Software Development Lifecycle (SDLC) (design, implementation, testing, delivery and operations), based on definitions from more senior roles. • Advises immediate management on project-level issues • Guides junior engineers • Operates with little day-to-day supervision, making technical decisions based on knowledge of internal conventions and industry best practices • Applies knowledge of technical best practices in making decisions Minimum Qualifications: • 3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience. Additional Responsibilities & Preferred Qualifications: We're looking for a hands-on AI professional with strong research and development skills. In this role, you will drive the research, development and continuous improvement of our AI solutions, from initial exploration through to production. What you'll do • Research, prototype and deliver new LLM-based solutions, and continuously improve existing ones. • Design experiments and evaluation frameworks to confirm that AI solutions perform as intended. • Maintain and monitor AI services and data pipelines in the cloud, performing data analysis and error analysis to continuously improve performance. • Identify opportunities where AI tools can support teams across the organization. • Present results and recommendations clearly to technical and non-technical stakeholders. Requirements • 3+ years of hands-on experience in software engineering, ML engineering or applied AI • Excellent Python and strong programming fundamentals • A track record of production-ready code: reliable, tested, observable systems. • Hands-on experience with LLMs: prompting, structured outputs, evaluation and cost control • Experience with AI agents, both building agentic workflows and using AI coding agents • Strong data science foundations: experimental design, evaluation metrics, error analysis, building ground-truth datasets, data analysis and cleaning, statistics, and data visualization • Hands-on experience with AWS (e.g. Lambda, ECS), SQL and PySpark. Nice to have • Experience with Databricks & Azure OpenAI • Background in e-commerce or product data• Experience with image processing and third-party vision APIs Subsidiary: PayPal Travel Percent: 0 PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. When making an application directly, we will never ask you to share passwords, one-time passcodes (OTP), or verification codes. Any such request is a red flag and likely part of a scam. All communication regarding your application will come from official PayPal email domains. If you suspect fraudulent activity, please report it immediately. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us. For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits: At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset-you. That’s why we offer comprehensive, choice-based programs, to support all aspects of personal wellbeing—physical, emotional, and financial—delivering meaningful value where it matters most. We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health. Who We Are: Click Here to learn more about our culture and community. Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at [email protected]. Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply.

What We're About Apiiro is the Agentic AppSec Platform built to transform how development teams design, develop, and deliver secure software. Powered by Deep Code Analysis, we give security and engineering teams the risk context they need to ship fast without cutting corners. As pioneers in ASPM, we're not just keeping up with the AI era. We're defining what secure development looks like inside it. About the Team Our R&D teams build and own the features that power Apiiro's platform — from deep code analysis to risk detection to developer-facing workflows. AI isn't a separate initiative here; it's how we build. Every engineering team at Apiiro is actively embedding LLMs, AI agents, and generative AI into the products they own, moving from experimentation to production and keeping things running reliably once they're there. What You Will Do • Build and ship end-to-end AI-driven features and agentic workflows- from experimentation through validation to production deployment (Python and C#). • Design scalable backend services that support production-grade agentic AI capabilities. • Develop and improve solutions powered by LLMs, AI agents, multi-agent systems, and generative AI frameworks. • Evaluate agentic architectures and model performance, owning monitoring, reliability, and continuous improvement in production. • Collaborate cross-functionally with software engineers, data scientists, and analysts to drive AI innovation across the platform. What You're About • 5+ years of hands-on backend software engineering experience. • B.Sc. in Computer Science or equivalent practical experience. • Proven experience building LLM-powered applications, AI agents, or generative AI systems using modern AI/ML frameworks. • Self-driven and comfortable operating in a fast-paced environment — you don't wait to be told what to do next. • Strong collaborator with clear communication skills; you thrive in diverse, cross-functional teams. • Hands-on experience with multi-agent architectures or agentic evaluation frameworks (preferred). • Familiarity with C# or polyglot engineering environments (a plus). What We Stand For at Apiiro Customer-First. Our customers are partners, not just clients. We anticipate their needs, go above and beyond to prove business outcomes, and measure our success by theirs. Excellence Mindset. We set the bar high, embrace challenges with curiosity, and never settle. Good enough isn't in our vocabulary. OneTeam. One mission, collective ownership, no silos. Our strength is in how we show up for each other and for our customers. Accountability. We own our actions, our commitments, and our results. Integrity and follow-through are built-in.

Make Your Mark Cymulate’s Continuous Security Validation enables companies to challenge, assess and optimize their cyber-security posture against the evolving cyberthreat landscape, simply and continuously. With world-class clients we strive to bring the highest level of service to everything we do. Our team is made up of the very best people for the job and as we grow, we’re always on the lookout for people with the skills, experience, and personality that will let us both shine. With high scores on Gartner, G2 and Glassdoor, our clients and employees have let us know what they love about us. What will you do • Design, build, and maintain production-grade AI-powered applications and services. • Develop end-to-end full-stack solutions, including backend services, APIs, and modern React-based frontends. • Build scalable, secure, and highly available distributed systems. • Develop AI agents, copilots, autonomous workflows, and intelligent automation. • Build and deploy RAG (Retrieval-Augmented Generation) solutions and integrate LLMs into production. • Design AI orchestration workflows using frameworks such as LangChain, LangGraph, or similar. • Implement AI evaluation, tracing, and observability pipelines using Langfuse or equivalent tools. • Develop MCP (Model Context Protocol) integrations and AI tooling ecosystems. • Build and maintain cloud infrastructure, CI/CD pipelines, and Infrastructure-as-Code. • Drive engineering productivity through AI-assisted development and automation. • Collaborate closely with Product, Design, and Engineering teams to deliver customer value. • Research and evaluate emerging AI technologies and introduce innovative solutions. • Own features end-to-end—from architecture and development to deployment, monitoring, and continuous improvement. What will you have • 5+ years of experience building scalable, production-grade full-stack applications. • Strong hands-on experience with TypeScript, Node.js, Python, React, and modern full-stack development. • Experience building AI-powered applications using LLMs (OpenAI, Anthropic, Gemini, etc.). • Hands-on experience with AI Agents, RAG, vector databases, prompt engineering, context engineering, and MCP. • Experience with AI frameworks such as LangChain, LangGraph, Langfuse, LlamaIndex, or similar. • Strong understanding of distributed systems, microservices, APIs, and cloud-native architectures. • Experience with AWS, Docker, Kubernetes, CI/CD, and DevOps best practices. • Ability to quickly learn and adopt emerging AI technologies and AI-assisted development tools. • Strong ownership mindset with the ability to independently deliver solutions from concept to production. • Experience building internal AI platforms or AI developer tools (advantage). • Familiarity with AI coding assistants such as Cursor, Claude Code, Windsurf, or GitHub Copilot (advantage). • Experience with multi-agent systems and autonomous workflows (advantage). • Background in SaaS or cybersecurity environments (advantage). • Experience leading technical initiatives or mentoring engineers (advantage). • Knowledge of AI security, model safety, and governance best practices (advantage). • Excellent communication skills, a collaborative mindset, and the ability to thrive in a fast-paced startup environment. • Passion for AI, curiosity, and a strong focus on innovation, execution, and business impact.