AI Engineer jobs in Tel Aviv-Yafo

Job Description You'll be a senior engineer on a deliberately flat, entrepreneurial team. Day to day you'll design and build agentic AI systems - agents, workflows, the orchestration layer that ties them together, and the infrastructure that makes all of it reliable at scale. This is hands-on building, not oversight. What you'll do • Design and build agentic workflows and the AI systems behind them - agents, the orchestration layer, and the infrastructure that runs them reliably • Take significant, ambiguous areas of the system and drive them from rough idea to working capability • Help scale the platform from a first working workflow to something used across the marketing organization • Contribute to evaluation, quality, and reliability - making sure systems don't just run, but run well • Work directly with the people who'll use what we build, and translate their needs into systems Qualifications • Substantial software engineering experience, with a track record of building and shipping complex systems • Hands-on experience building agentic or LLM-based systems - this is a requirement, not a nice-to-have. We’re looking for someone who has designed agent workflows, wrestled with prompts and context, handled the failure modes, and shipped something real • Strong product instincts: comfortable with ambiguity, able to define a problem before solving it, and opinionated about what's worth building • Comfort working in a small, flat, fast-moving team where you set much of your own direction • The ability to communicate clearly with non-technical partners across marketing Nice to have: • Experience with orchestration frameworks for agentic systems (e.g. LangGraph or similar) • Experience with evaluation frameworks, RAG, or working with knowledge bases at scale • Familiarity with the marketing domain, or a genuine interest in it • Experience taking a system from early prototype to broad organizational adoption Additional Information We're a small, fast-moving team building the AI systems that are changing how Wix's marketing organization works. Our goal is to take Wix marketing into the agentic era, where marketers are supported end-to-end by AI that carries real work from start to finish. This is a rare chance to build agentic AI that's actually in production and actually changing how a large organization works. Not a demo and not a proof of concept. You'll have real ownership, work alongside experienced engineers on genuinely hard problems, and help define what an AI-native marketing organization looks like. For more Information feel free to talk to Sasha Belenky.

Job Description As an AI Engineer, you'll work on cutting-edge technologies, tackle challenging technical problems, and influence the engineering culture at Base44. You'll become an industry leader in AI-native development while improving your skills and collaborating with top-notch engineers. You'll be part of a team that lives and breathes AI, redefining how software is built from the ground up. In your day-to-day, you will: • Work on cutting-edge technologies and become an industry leader • Use AI to bridge ideation to production in record time without compromising on code quality, security, or architecture. • Improve your skills and learn from top-notch engineers • Tackle tough problems and find creative ways to solve them • Push your code to millions of users every day • Solve tough technical challenges on a cutting-edge, AI-powered platform • Influence our engineering culture by contributing to internal knowledge sharing and, if you're interested, the open-source community Qualifications • 7+ years of software engineering experience in tech-first product companies or high-growth startups • AI-pilled daily workflow: You use AI coding tools as your primary workspace, leveraging AI across the full software lifecycle (planning/design, implementation, testing, refactoring, maintenance) while maintaining high standards for architecture, quality, security, scalability, and reliability • Hands-on with agents in production: tool calling, context management, evals, and cost and latency tradeoffs. Additional Information We’re Base44, a newly acquired part of Wix, on a mission to change how products and apps get built. Our AI-powered platform allows anyone to create custom applications using natural language—no traditional coding required. We operate like a startup within Wix: fast-moving, collaborative, and focused on solving complex problems with simple, elegant solutions. We’re here for anyone who wants to build: creators, solo founders, startups, entrepreneurs, side hustlers, and everyone in between. Whether you're launching a product, validating a concept, or chasing a hunch, Base44 gives you the power to make it real.

Vi is an enterprise AI platform for health enterprises – healthcare, biopharma, and wellness. We deploy agentic AI and predictive models into production environments where the output drives next best actions for patients, care teams, and operations to deliver ROI and improve health outcomes. Data Web is the data foundation under the platform – the third-party health and consumer data we license, resolve, and turn into assets our customers and our models run on. We are looking for an AI Engineer to own that path end-to-end, from ingestion and identity resolution through features, retrieval, and production delivery, and to own the read on what comes out of it. Reporting directly to the VP of R&D, the AI Engineer is a hands-on IC role at the crossroads of data science and data engineering. You build the data, you build the AI that runs on it, and you judge the result. Responsibilities Build and own data pipelines: Monitored ingestion for high-volume third-party health and consumer feeds. Put AI to work on the data itself: LLMs and ML for parsing, normalizing, classifying and matching. Build the feature and retrieval layer: Versioned features, embeddings and retrieval our models and agents run on. Evaluate: Implement evaluation frameworks, benchmarks, and metrics to track performance. Build across the stack: Builder mindset – comfortable with Backend services and internal tooling. Do the first read on what you build: Is there signal, and what is this asset good for and turn data assets into products. Partner cross-functionally: Turn product, client and compliance requirements into production systems. Requirements 3+ years of overall software experience, including background in Data Science, ML modeling, and shipping production-grade data systems. Production AI & Data Science: experience building ML/DS models, evaluating data signals, and deploying the underlying data systems required to run them in production. Production LLM & AI Engineering: Hands-on experience shipping LLM capabilities combined with an AI-first development workflow. ETL/ELT pipelines and Lakehouse architectures using Python, SQL, Spark on AWS (Glue, EMR, Athena, Iceberg). Software & DevOps: Strong backend engineering fundamentals, CI/CD, Docker, workflow orchestration, and Infrastructure as Code (AWS CDK/CloudFormation). High Ownership & Velocity: High agency, a strong sense of urgency, and full lifecycle ownership of production systems from architecture to monitoring.

Who are we? Skai (formerly Kenshoo) is a leading omnichannel marketing platform that leverages advanced AI and data-driven performance media to enable smarter decision-making, increased efficiency, and maximized ROI for businesses worldwide. Our platform helps manage approximately $10B in annual ad spend through partnerships with Google, Meta, Amazon, Microsoft, and others. Founded in 2006, Skai is a global company with around 650 employees. We operate in a hybrid work model that combines remote flexibility with in-office collaboration. What will you do? As an AI Engineer, your primary focus will be delivering working features while adopting a Builder Mindset to shape the future of software development at Skai. You will leverage cutting-edge GenAI tools (such as Claude Code and others) to accelerate development, streamline workflows, and bring high-quality, production-ready features to life. In this role, you will work closely with PMs, designers, and fellow engineers across frontend, backend, and data domains. You will use AI to tackle complex debugging, conduct research, and eliminate repetitive tasks—continuously improving your productivity while delivering functional, impactful features within your pod. Responsibilities: Feature Delivery: Own and deliver working features from end to end, contributing production-ready code with guidance and driving tangible product value. AI-Accelerated Development: Utilize GenAI tools (e.g., Claude Code) to accelerate feature development, improve personal productivity, and optimize daily workflows. Problem Solving & Debugging: Leverage AI for rapid debugging, technical research, and reducing repetitive manual work during feature delivery. Cross-Domain Collaboration: Build a solid understanding across product, frontend, backend, and data domains, collaborating effectively with PMs, designers, and engineers. Context & Documentation: Document technical decisions clearly and contribute to building shared team context and knowledge bases. Continuous Learning & Adaptability: Learn the tech stack quickly, adapt smoothly to new tools/workflows, and actively apply feedback to grow as a builder. Pod Reliability: Act as a dependable, collaborative contributor within your pod, helping drive team momentum and execution. Requirements 2–5 years of experience in software development. Relevant Academic Degree (B.Sc. in Computer Science, Software Engineering, or related fields) OR Relevant Military Experience (e.g., tech/intelligence units such as 8200, Mamram, Ofek, etc.). Builder Mindset: Strong passion for GenAI tools (such as Claude Code, etc.) and a proven desire to integrate them into daily coding workflows. Ability to quickly learn new tech stacks, adapt to changing tools, and translate feedback into rapid growth. Strong cross-domain curiosity - eager to understand product context, backend logic, frontend UX, and data flow. Excellent communication skills and a strong collaborative mindset in a hybrid working environment.

We're looking for an experienced AI Engineer to join our core team and design, build, and implement the autonomous AI agents that power Echo's revolutionary approach to eliminating container vulnerabilities at the source. Responsibilities: • Explore and prototype cutting-edge AI techniques to tackle our hardest challenges • Architect and develop autonomous AI agents that intelligently eliminate vulnerabilities during container image generation • Collaborate with product and engineering teams to bring AI-driven features from concept to production • Monitor and evaluate AI model performance, implementing feedback loops to continuously improve accuracy and reliability • Develop and maintain machine learning pipelines that process security data and generate actionable insights • Ensure AI systems are robust, reliable, and performant at enterprise scale Requirements: • 3+ years of hands-on experience with AI or machine learning frameworks • 4+ years of experience as a Software Engineer • Experience deploying and scaling AI/ML models in production environments • Proficiency with cloud platforms, particularly AWS, for AI/ML workloads • Excellent communication skills and proven ability to work effectively in cross-functional teams • Strong problem-solving skills and ability to translate business requirements into technical AI solutions

About BlackEdge Labs BlackEdge Labs is the technology and innovation arm of BlackEdge, a growing publicly traded financial group operating across mortgages, payments, and corporate financing. We build the software, data, AI, and digital platforms that support the Group's operations, growth, and future financial solutions, combining deep technological expertise with a practical, business-oriented approach. About the role We're looking for a Senior AI Developer to join BlackEdge Labs and build the LLM-powered products and agentic systems that run in production across the Group. The role is centered on applied AI engineering: designing and shipping agents, RAG pipelines, and tool-calling workflows; building the evaluation, guardrail, and observability layers that make them reliable in a regulated environment; and driving an AI-assisted engineering lifecycle in which coding agents are a core part of how we build software. This is a hands-on, applied engineering role — you'll write production Python, own features end-to-end, and set the standard for how AI is built and used across our engineering teams. It is not a research or data-science position. What you'll be doing Designing, building, and deploying LLM-powered capabilities — agents, RAG, tool calling, structured extraction, and workflow integrations — using Python, FastAPI, LangGraph, and Azure. Building evaluation suites, guardrails, and observability for LLM systems: measuring output quality, catching regressions, and optimizing cost and latency. Owning product features end-to-end — from requirements and technical design through implementation, code review, testing, and production rollout — using AI coding agents throughout the workflow. Designing and maintaining internal AI development tooling: coding-agent skills and plugins, AI-assisted development pipelines, and standards for reviewing, testing, and securing AI-generated code. Leading technical design reviews and architectural decisions for agentic and distributed systems. Building the event-driven backend services these capabilities run on, with the resilience, observability, and security required in a regulated financial environment. Working closely with Product and business stakeholders to translate requirements into well-scoped AI solutions. Mentoring engineers on effective and responsible use of AI throughout the development process. What you'll need 4–5 years of hands-on backend / software engineering experience, including real production experience building LLM-powered systems. Strong proficiency in Python and experience building scalable, resilient, and secure APIs and services. Production experience with LLM APIs (Azure OpenAI, OpenAI, Anthropic, or similar): tool calling, structured outputs, prompt design, cost and latency optimization. Hands-on experience building agents with LangGraph, Semantic Kernel, or a similar agent framework. Experience designing and implementing RAG pipelines — chunking, embeddings, vector search (pgvector, Azure AI Search, or similar), and retrieval quality tuning. Experience evaluating LLM systems: building eval sets, measuring output quality, and catching regressions before production. Hands-on experience using AI coding agents (Claude Code, Cursor, GitHub Copilot) in production codebases, including reviewing and correcting AI-generated code. Working knowledge of asynchronous processing, event-driven architecture, and cloud/DevOps practices (CI/CD, Infrastructure as Code, monitoring). Strong security and compliance awareness — PII handling, secrets management, and auditability — including as applied to LLM inputs and outputs. Strong problem-solving, ownership, and communication skills, with the ability to lead technical discussions with technical and business stakeholders. Strong communication skills in Hebrew and English. Nice to have Experience with multi-agent systems, MCP, or building internal developer tooling, SDKs, or platform capabilities. Experience with fine-tuning, model routing, or running open-weight models. Experience with elastic, PostgreSQL, and message brokers such as Azure Service Bus. Experience in FinTech, lending, real-estate underwriting, or another regulated environment. Experience with Hebrew/RTL document processing or OCR pipelines. M.Sc. in Computer Science, Software Engineering, or a related field. Ready to build AI-powered products and development capabilities that shape how software is built across a growing publicly traded financial group? We'd love to meet you. This is a full-time, office-based position at our Tel Aviv office. The position is open to candidates of all genders.

Conifers is transforming security operations centers (SOCs) with CognitiveSOC™, its AI SOC platform, enabling enterprises and MSSPs to achieve SOC excellence. By leveraging agentic AI, Conifers helps security teams investigate complex, multi-tier incidents with speed, accuracy, and trust. Led by seasoned cybersecurity leaders and backed by SYN Ventures, PICUS Capital, and others, the company brings deep industry knowledge and innovation to an increasingly AI-driven threat landscape. We’re building an AI-native security platform that enables autonomous agents to investigate real-world threats at a massive scale. About The Role : You’ll build real AI systems running in production, where intelligent agents and robust backend architecture work together to investigate security incidents for real customers. If you enjoy turning cutting-edge AI into reliable, scalable production systems, you’ll feel at home here. What You’ll Do : • Design, build, and ship major end-to-end features • Lead development of AI agents operating in production environments • Architect and scale Python-based distributed backend systems • Make key technical decisions that shape the evolution of an AI-first platform • Build systems that combine LLMs, reasoning flows, orchestration, and classic backend engineering • Work closely with Product, Design, Security Researchers, and GTM teams • Bring clarity, ownership, and strong engineering standards to the team What You’ll Bring : • 5+ years of software engineering experience • Strong software engineering background, with the 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 • Experience designing systems that balance AI components with reliable backend infrastructure • Ability to take ambiguous problems and turn them into structured, scalable solutions • Strong ownership mindset and bias for action • Full professional fluency in English Nice to Have : • Experience in the cybersecurity domain • Experience building security or AI-driven products • Experience working in a fast-paced startup environment Our Commitment : We are an equal opportunity employer and value diversity at our company. All qualified applicants will receive consideration without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. #LI-AM1 #LI-Hybrid

We've come a long way since we first opened our doors, but our mission has always stayed the same: to provide world class solutions for the travel industry. Travel Booster is a constantly improving ERP solution that frees users from the complexities of creation so they can do more, faster. We are looking for a hands-on engineer to own our cloud infrastructure and CI/CD pipelines on AWS with Azure DevOps (Pipelines & Releases). You will take over existing infrastructure and pipelines written in PowerShell and Python, stabilize & improve them, and lead AI/LLM enablement across Dev, QA, and Support, including building internal agents, integrating with LLMs (via MCP and other frameworks), and driving AI adoption in day-to-day workflows. You'll partner closely with R&D to streamline builds, deployments, environment management, and observability, while also pushing upgrades and optimizations in AWS services. What will your job look like? Key Responsibilities CI/CD & Cloud Infrastructure Own, maintain, and enhance Azure DevOps Pipelines & Releases (multi-stage YAML/classic) for builds, deployments, and scheduled tasks. Refactor existing PowerShell, javascript and Python pipeline scripts for reliability, security, and performance. Implement pipeline templates, gates, approvals, artifact versioning, and automated rollbacks. Introduce pipeline observability (dashboards, alerts, metrics) and enforce branching, tagging, and release standards. Operate and improve AWS environments (Prod/Stage/Dev/QA), including networking, compute, storage, databases, security, and cost management. Implement Infrastructure as Code (IaC) (Terraform or AWS CloudFormation); manage parameter stores/secrets. Automate environment lifecycle: provisioning, configuration, blue/green & canary releases, and disaster recovery. Drive updates and improvements across services (e.g., EKS/EC2/Lambda, RDS/DynamoDB, ElastiCache, S3, CloudFront/ALB/ELB, Route 53, CloudWatch, Systems Manager, IAM, KMS). Standardize and automate Dev/QA/SIT/UAT environments; ensure parity with Production where relevant. Build ephemeral preview environments per PR; manage test data seeding/anonymization. Collaborate with QA to integrate test orchestration (smoke/regression) into pipelines with gates and quality metrics. Implement monitoring/alerting (CloudWatch, Prometheus/Grafana), logging (CloudWatch Logs/OpenSearch), and distributed tracing (X-Ray/OpenTelemetry). Harden IAM (least privilege, scoped roles), secrets management, key rotation, and compliance checks. Track and optimize AWS spend (rightsizing, autoscaling, lifecycle policies). AI/LLM Enablement Build and deploy AI-powered features using LLMs (OpenAI, Azure OpenAI, Hugging Face). Implement MCP-based integrations for context-aware workflows. Design and build internal AI agents (for Dev/QA/Support) to assist with triage, runbooks, test data generation, log analysis, and developer productivity. Integrate LLMs via secure patterns (e.g., Model Context Protocol (MCP), retrieval-augmented generation, prompt engineering, guardrails, and observability). Create tooling that plugs AI into pipelines/workflows (PR summaries, release notes, changelog generation, incident post-mortems). Establish data governance for AI: access control, PII handling, prompt/data sanitization, and auditability. Write production-grade code for AI workflows, including prompt engineering, function calling, and agent orchestration. Integrate AI services into ERP, web apps, and backend systems. Requirements All you need is... Required Skills & Qualifications 5+ years working with AWS in production (multi-account, multi-env). 3+ years with Azure DevOps (Pipelines/Releases), including YAML pipelines. Strong javascript, PowerShell and Python for automation and pipeline tasks. Hands-on experience with IaC (Terraform or CloudFormation). Solid understanding of networking, security (IAM/KMS), containers (Docker; EKS preferred) or serverless (Lambda). Experience integrating LLMs/AI into engineering workflows (agents, prompt engineering, RAG, MCP or similar). Proven track record of CI/CD best practices, release orchestration, artifact/version management, and rollback strategies. Experience with OpenAI/Azure OpenAI, Anthropic, or other LLM providers; familiarity with MCP. Knowledge of Node.js build/deploy pipelines (to align with parts of our stack). Exposure to C++ build systems (beneficial for our business logic components). Observability stack: OpenTelemetry, Grafana, Loki/ELK/OpenSearch. Security/compliance tooling (e.g., CIS benchmarks, AWS Config, Inspector). Experience with fine-tuning and deploying models in production. Excellent interpersonal skills, Proactive, Fast learner and team player Knowledge in Agile and Scrum - Advantage Excellent English writing and verbal skills - Mandatory Travel Booster is an equal opportunity employer. We welcome applicants from all backgrounds and are committed to fostering a diverse and inclusive workforce

About Us Novee is the AI penetration testing platform built for a world where attackers operate at machine speed. Founded in Tel Aviv in April 2025 by a team with decades of nation-state offensive security experience - including veterans of Unit 8200, Iron Dome, and elite zero-day research - we're turning that expertise into a platform that thinks like a real attacker, runs continuously, and uncovers the novel vulnerabilities that manual testers and scanners miss. We raised $51.5M in four months, backed by top investors YL Ventures, Canaan Partners, and Oren Zeev - one of the fastest funding trajectories in offensive security. Our proprietary AI model outperforms frontier LLMs by over 55% on real exploitation benchmarks, and we're just getting started. We're looking for exceptional people to join our mission: making continuous, intelligent offensive security the new standard. About the Role We're hiring an AI Engineer to design and build the intelligence layer behind our autonomous offensive security platform. You'll develop AI agents capable of performing vulnerability discovery and exploitation at the level of top human white-hat hackers – combining deep security expertise with advanced AI reasoning and decision-making. This role, reporting directly to our Agent TL, offers the opportunity to define how AI transforms offensive cybersecurity. You'll collaborate closely with AI researchers, software engineers, and security experts to translate penetration-testing workflows into intelligent, automated capabilities – systems that plan, execute, and adapt in real time. If you're passionate about AI, thrive in fast-paced environments, and want to shape the future of autonomous cybersecurity - we'd love to meet you. Responsibilities Design and implement autonomous AI agents for penetration testing and vulnerability exploitation. Translate offensive security workflows into intelligent, multi-step reasoning systems. Develop modules for exploit generation, payload delivery, and adaptive vulnerability scanning. Collaborate with AI researchers to fine-tune and evaluate models that enhance reasoning, adaptability, and precision. Build evaluation frameworks to measure exploit success, learning performance, and reliability. Ship production-ready AI systems that improve the speed, depth, and scalability of security testing. Establish best practices for safe and controlled deployment of AI agents in offensive environments. Requirements 3+ years of hands-on experience in machine learning, AI engineering, or cybersecurity development. Strong understanding of penetration testing, vulnerability research, and exploitation techniques. Builder mindset - thrives in fast-paced, early-stage startup environments with full ownership. Proficiency in Python, with experience building automation frameworks, orchestrators, or integrations. Proven ability to deliver production-grade AI systems (CI/CD, monitoring, rollback, scalability). Bonus Points Experience building AI agents or orchestration frameworks. Background combining AI models with offensive security tools. Contributions to open-source projects in cybersecurity, exploit development, or agentic AI systems. Advanced degree (M.Sc/Ph.D.) in Computer Science, Cybersecurity, or related technical field. What We Offer The chance to shape the core intelligence of a next-generation cybersecurity platform. A collaborative, world-class team of AI engineers, researchers, and security veterans. Freedom to innovate and experiment with the latest in AI-driven autonomy. End-to-end ownership and direct impact on the company's technology and vision. Competitive compensation, growth opportunities, and the excitement of joining an AI-first cybersecurity startup at its foundation.

About Us OurRitual is a fast-growing digital platform revolutionizing relationship guidance. We provide expert-led sessions, personalized pathways, and engaging content to help individuals and couples work through relationship challenges. We are now scaling and looking for the right people to join our (great!) team to continue delivering exceptional experiences to our users. Role Overview We are looking for a Generative AI Engineer to lead our AI efforts end-to-end — from infrastructure and production systems to internal adoption and cross-team enablement. You will play a significant role in building the world's first Consumer Therapy AI Product (someone said RAG? But we mean a real one that works in production...). This is a critical role in a high-growth, fast-paced B2C startup, requiring a leader who can advocate for Engineering requirements, tech-debt and best practices while promoting a product-mindset and putting our customers front and center. About You • You are a great human being and you’re all into teamwork. you care about how people will feel inside the organization and set high standard for culture, professionalism and maturity. • A Doer, hands-on, biased for action and not taking an advisory role. Know how to translate challenges into actions. Able to work both individually and manage multiple priorities while driving others around you for action. • You're a fast learner, jack of all trades, feel comfortable in a fast paced, ever-changing environment. You can break down complex problems into steps and plot clearly how to get from A to Z while having the ability to zoom out and see the bigger picture. • You are an experienced hands on engineer, with proven experience with Developing LLM based products, with a real passion to AI and LLM, eager to learn about very new model and technology in this domain, and have a real understanding of the AI ecosystem. Key Responsibilities AI Infrastructure & Production • Own and design GenAI architecture (LLMs, pipelines, agents) • Build and ship AI features into production • Integrate enterprise models (OpenAI, Anthropic, Google) • Optimize cost, latency, and reliability (tokens, caching, evals) • Handle real-world constraints (context window, hallucinations) Prompt Engineering & Product Collaboration • Lead prompt design and experimentation across teams • Work with product, copy, and operations on AI-driven features • Build and evaluate prompt pipelines (quality, consistency) Research & Innovation • Stay up to date with GenAI ecosystem (models, tools, frameworks) • Evaluate and implement frameworks (LangGraph, LangChain, etc.) • Prototype quickly and iterate in a startup environment Required Skills & Qualifications • ~1+ year experience with Generative AI / LLMs • 5+ years experience with Backend engineering • Experience shipping GenAI features to production • Strong hands on, production grade backend/software engineering skills (Python preferred) • Experience with major AI providers (OpenAI, Anthropic, Google) • Prompt engineering and LLM behavior knowledge • Understanding Agents / multi-step workflows • Experience with AI frameworks (LangChain, LangGraph, etc.) • Familiarity with embeddings / vector databases • Excellent problem-solving skills with demonstrated success in fast-paced environments. Bonus • MLOps / model deployment experience • Evaluation, monitoring, and guardrails • Fine-tuning or model customization • RAG systems (Retrieval-Augmented Generation) • Building retrieval pipelines and grounding LLM outputs

We're reimagining enterprise Identity and Access Management from the ground up. Founded by serial entrepreneurs Shai Morag and Tal Marom and backed by a $60M seed round from Greylock, Accel, and CRV, we're building the next generation of identity security. Identity is the gateway to everything- who's let in, who's kept out, and it's now the number one attack vector in the enterprise. The tools built to govern it were designed for a slower world of human users and static environments. That world is gone. Identities are exploding across human, machine, and AI agents faster than legacy systems can track, and security teams are left patching together five disconnected tools that still can't answer "who has access to what, right now." We think the answer isn't another point solution- it's a new foundation. Oak is the AI-native Identity Operating System: an AI connector framework that reaches any application, a live identity graph built from raw evidence, and a team of AI agents that governs the full lifecycle of every identity in one platform. We're building Oak's AI-native core from day one-engineered for what enterprise identity is becoming, not patched onto what it used to be. And we're just getting started. At Oak, agents are core to what we build - We're looking for an AI Engineer to design and own the agentic infrastructure that spans the entire company What You'll Do • Architect and ship agentic capabilities as production-grade product features - owning the full tradeoff space across reliability, observability, security, latency, deterministic behavior and cost. • Design and build AI agents that operate across Oak's identity graph, automating complex identity related workflows. • Evaluate and integrate emerging LLMs, agent frameworks, and agent infrastructure, making principled build-vs-integrate decisions grounded in production requirements. • Partner with R&D and product leadership to identify where agentic automation delivers the highest leverage across the product. What You'll Bring • 8+ years of backend engineering in high-level programming languages (e.g., Go, Python), with a proven track record of solving hard technical problems. • Hands-on experience building and shipping production LLM agent systems with frameworks like LangGraph, Strands Agents, or ADK, and with model gateways/routing layers. • A low-ego, high-impact approach: You are self-directed, driven by delivery, and willing to roll up your sleeves for the foundational work that ensures system stability. • Deep architectural pragmatism: Extensive experience with microservices, databases, and asynchronous systems, coupled with a nuanced understanding of exactly when and how to deploy them. • Forward-thinking adaptability: A continuous desire to explore new technologies, leveraging modern development tools and AI paradigms to accelerate your workflows and multiply your impact. • Bachelor of Science in Computer Science, Software Engineering, or equivalent battle-tested experience.

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.

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.

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.

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.

We're building an agentic AI platform that helps enterprises transform complex business workflows into AI-powered operations. We work with leading global companies to identify high-value workflows, deploy AI agents into real business environments, and help organizations move from experimentation to measurable enterprise impact. We believe AI adoption inside the enterprise isn't just a technology challenge. It requires business context, workflow understanding, change management, trust, ownership, and a clear path to value. That's where this role comes in. We are a well-funded, early-stage startup, looking for a talented and motivated AI Engineer to join our team. The focus of this role is to develop advanced AI agents aimed at automating and optimizing low-skill human tasks, with a special emphasis on document processing, data extraction, text and email comprehension, and related workflows. You will be responsible for researching, designing, and deploying AI solutions that can replace repetitive manual tasks, improving efficiency and scalability for organizations. Your Impact AI Agent Development • Design, develop, and implement AI agents using best of breed LLMs to automate document processing tasks across enterprise workflows. Workflow Automation • Build machine learning pipelines to automate content-heavy processes for enterprise businesses. Model Optimization • Fine-tune and optimize pre-trained LLMs to accurately interpret, classify, and process large volumes of documents, improving speed and accuracy. Collaboration • Partner with product, engineering, and business teams to identify high-value automation opportunities and integrate AI-driven solutions into our operations. Evaluation & Testing • Develop metrics and conduct extensive testing to ensure reliability and efficiency of the AI systems in real-world scenarios. What It Takes Experience • 5+ years of experience as a software engineer or data scientist building production systems. • 2+ years of experience with large language models and NLP techniques. • Background in developing AI agents for content heavy tasks. • Experience with multiple LLM Vendors, RAG or Fine Tuning OSS or Commercial models. Technical Skills • Proficiency in Python and machine learning libraries such as TensorFlow or PyTorch. • Deep understanding of LLM architectures and NLP applications like entity recognition, document classification, and summarization. • Experience with model grounding techniques, retrieval-augmented generation (RAG), and deploying robust AI models in production environments. • Skills in designing and deploying AI models through APIs, containerization (Docker, Kubernetes), and cloud platforms (AWS, GCP, Azure). • Understanding of best practices for continuous monitoring, evaluation, and iterative improvement of deployed models.