AI Engineer jobs in Israel

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.

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.

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 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.

About Brandlight Brandlight is the leading enterprise AI visibility platform, built to help the world's leading brands understand, manage, and optimize how they appear across AI-driven search, commerce, and advertising. As AI rapidly becomes a trillion-dollar marketing and distribution channel, Brandlight is defining the systems that decide how brands are surfaced, trusted, and chosen. Join our team and help build the next generation of tools shaping the future of brand management in an AI-first world. About the Role We're looking for a Senior Applied AI Engineer who combines deep data science expertise with the engineering skills to turn research into reliable, production-ready products. You'll be a hands-on technical leader, owning significant AI capabilities from problem definition, academic survey, and system design through research, experimentation, deployment, and continuous improvement. Your work will span classical machine learning, large-scale data analysis, and AI agents that power brand intelligence, market research, and performance marketing. You should have a track record of driving complex projects, not just contributing to them, and be comfortable making technical decisions, navigating ambiguity, and delivering in a fast-moving startup environment. You'll build systems that Fortune 500 marketing teams rely on to make consequential business decisions. Responsibilities Own AI capabilities end to end. Translate business and product needs into well-defined problems, research plans, and technical designs. Take solutions from initial exploration through production deployment and ongoing improvement. Develop and improve our core algorithms. Build production-grade AI agents - performance marketing, market research agents, auto-ML agents. Turn research into maintainable software. Build reusable modules, data pipelines, and services with clear interfaces, automated tests, and robust deployment practices, not just standalone prototypes. Own quality and performance in production. Monitor system behavior, investigate failure cases, and continuously improve accuracy, reliability, latency, and cost as usage and data volumes grow. Drive technical decisions and execution. Choose the right approach for each problem, balancing statistical methods, classical ML, and LLM-based systems. Make explicit trade-offs between research depth, delivery speed, and operational complexity. Provide hands-on technical leadership. Partner with product and engineering to shape priorities, lead technical initiatives, review designs and code, and mentor teammates. Requirements MSc or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field. 5+ years of experience in data science or applied machine learning, plus 2+ years in ML engineering or software engineering, with direct responsibility for deploying and maintaining production systems. Proven ownership of significant AI products or features. You have been a primary technical driver, taking ambiguous problems from initial concept to a working product used by real customers. Strong foundations in machine learning and statistics, including experimental design, model evaluation, and practical experience with NLP, embeddings, clustering, or related methods for analyzing unstructured data. Strong Python, SQL and Typescript skills, alongside solid software engineering practices: modular architecture, automated testing, version control, code reviews, and maintainable production code. Hands-on experience building LLM-powered applications or AI agents beyond the prototype stage, including tool calling, structured outputs, context management, and systematic evaluation. Experience deploying and operating systems in a cloud environment, including containerization, CI/CD pipelines, logging, monitoring, and debugging production issues. Strong product judgment and independent execution. You can define milestones, prioritize experiments, communicate technical trade-offs, and collaborate effectively across product, engineering, and business teams in a fast-moving environment. Advantage Experience as a core technical contributor at a high-growth startup, building new products and scaling them as adoption grows. Experience in advertising technology, marketing analytics, search, information retrieval, ranking, or recommendation systems. Familiarity with agent frameworks and SDKs such as ADK, LangChain, or comparable tooling. Experience building systems where traceability, explainability, approval workflows, and reliable execution are important to customer trust. Why Join Us At Brandlight, you'll build and shape a new category at the intersection of AI, marketing, and commerce. We're a fast-growing startup led by repeat entrepreneurs, world-class engineers, and marketing leaders, all driven to reinvent how brands are built, discovered, and chosen in the age of AI.

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.

Unixi is revolutionizing Identity and Access Management (IAM) with our Universal SSO solution that seamlessly works with SaaS applications-without requiring traditional integrations. By removing complexity, eliminating the SSO tax, and giving organizations visibility and control over their SaaS ecosystem, Unixi is building a new kind of IAM platform for the modern enterprise. Now, with the introduction of Lifecycle Management (LCM), Unixi is expanding from a breakthrough access solution into a broader IAM platform – one that not only controls access, but helps organizations manage identity workflows and user lifecycle processes across their SaaS environment. We're a fast-growing, well-funded startup backed by industry-leading investors and cybersecurity pioneers, and we're looking for an exceptional AI Software Engineer / AI Agent Engineer to help us turn AI-driven product ideas into reliable, production-grade systems. As an AI Software Engineer at Unixi, you'll work on one of the most interesting problems in enterprise software: applying AI agents and multi-step workflows to real operational challenges in identity, access, and lifecycle management. This is not a research role. It is a hands-on engineering role for someone who loves building working systems end to end, from workflow design and backend integration to evaluation, reliability, and production readiness. You will help us increase our execution capacity around AI-driven product capabilities and remove bottlenecks in integrating, testing, and operationalizing production AI workflows. This is an opportunity to join early, work closely with product and engineering leadership, and help define how AI becomes a real part of the product rather than just a prototype. Responsibilities: Design and implement multi-step AI workflows and agentic systems for real product use cases. Integrate AI workflows with backend services, internal systems, external APIs, databases, and product data sources. Define runtime behavior, state management, retries, failure handling, and fallback logic for production-grade AI systems. Build ingestion and output flows for AI-driven product capabilities, including structured and unstructured data processing. Test, evaluate, and improve the quality, reliability, and determinism of AI workflows in production environments. Improve observability, tracing, maintainability, and operational readiness of AI systems. Collaborate closely with backend engineers, product leaders, and domain experts to turn ambiguous ideas into robust implementations. Help shape engineering best practices for agent orchestration, tool usage, security guardrails, and production AI architecture. Requirements: 4+ years of software engineering experience, with strong backend development skills. Strong Python experience and solid software engineering fundamentals. Hands-on experience building AI agents, LLM workflows, or orchestration systems in production or near-production environments. Experience with frameworks such as Google ADK, LangGraph, LangChain, or similar agent/workflow orchestration tools. Experience with Vertex AI or comparable cloud AI platforms. Experience integrating AI systems with APIs, databases, backend services, and external tools. Strong understanding of workflow execution concerns such as state handling, retries, failure recovery, and reliability. Experience testing and validating AI-driven systems beyond simple prompting or demos. Ability to move quickly, own problems end to end, and build production-quality systems in a startup environment. Strong communication skills and a practical, execution-focused mindset. Bonus: Background in cybersecurity, IAM, networking, or enterprise SaaS products – big advantage. Startup experience, especially in early-stage or 0-to-1 environments – big advantage. Experience with evaluations, prompt/version testing, and quality measurement for AI systems. Experience with observability, tracing, and monitoring tools for AI workflows. Familiarity with tool ecosystems, MCP-style integrations, or structured tool-calling architectures. Experience with browser automation, scraping, or complex data extraction workflows. Experience with multimodal or document-based workflows. Experience with security, guardrails, or abuse prevention for AI systems. Experience optimizing cost, latency, and performance of LLM-based production systems. Ready to make IAM better and more secure? Apply now and join our mission at Unixi!

Staff AI Engineer - Israel, R&D, Senior, Full time

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.

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!

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

Description DLP's rule-based framework is broken. We asked machines to find problems with rigid rules, then expected humans to investigate the noise - an impossible task. Jazz is the new model. It starts with total coverage from a forensic endpoint agent and uses a powerful Agentic Investigator that learns your business. It delivers clear, pre-investigated answers instead of alerts, and is designed to be run by a single person. Finally, DLP that works. We are seeking a Senior AI Engineer to build the intelligence layer for Jazz. In this role, you will solve core product challenges involving large language models and highly imbalanced security datasets. You will design and implement generative workflows and agent-based AI systems that operate reliably at production scale. What You’ll Do: • Drive the integration and production deployment of cutting-edge AI frameworks directly into our core product, unlocking the power of scalable, AI-powered applications that redefine our capabilities. • Design and implement generative workflows including agentic systems, tool-using LLMs, retrieval pipelines (RAG), and vector search infrastructure. • Build and deploy models for classification, generation, and embeddings tailored to real-world security use cases. • Develop automated testing, evaluation, and monitoring systems to ensure model performance and data quality in production environments. • Work across the full model lifecycle from experimentation and development to deployment, optimization, and maintenance. • Collaborate closely with product and engineering teams to integrate AI capabilities into the platform. • Contribute to high engineering standards and provide technical mentorship within the team. What We’re Looking For: • 4–6+ years of experience in machine learning engineering or applied AI, with a preference for an MSc in a relevant field. • Hands-on experience building and deploying large-scale production systems with machine learning components. • Practical experience with modern AI architectures, including LLMs, RAG pipelines, vector search, and prompt orchestration. • Strong backend engineering experience and familiarity with building production services. • Experience implementing and productionizing AI frameworks with automated testing, monitoring, and data quality controls. • Strong architectural thinking and algorithmic intuition for model selection, evaluation, and optimization. • Ability to work independently in fast-moving environments and take ownership of complex technical challenges. Why Join Jazz? • Work on complex problems at the intersection of AI, cybersecurity, and large-scale systems. • Build production AI systems that power a new approach to Data Loss Prevention. • Take ownership in an early-stage company where engineering decisions shape the product. • Collaborate with a team focused on solving hard technical challenges with high standards of engineering. Our office is at Sonol Tower in Tel Aviv, next to Carlebach train station.

Description A world-renowned leader in GPU acceleration, AI supercomputing, and end-to-end platforms powering generative AI, autonomous systems, digital twins, and large-scale data-center infrastructure used by virtually every major technology company is seeking an AI Developer to join a high-impact, rapidly growing Agentic AI initiative. This is a hybrid position based in Israel, requiring on-site presence in Yokneam three times a week, together with close collaboration with global teams, including occasional evening meetings as part of cross-site coordination. If you’re looking to deepen your hands-on experience with real-world AI systems, contribute to enterprise-grade Agentic AI solutions, and grow within a global, fast-evolving environment—this role offers a meaningful and exciting opportunity. What does a typical day look like? ב This is a hands-on role with significant learning and growth potential in advanced AI technologies. Key Responsibilities • Develop components within Agentic AI architectures, including multi-agent orchestration and RAG workflows • Implement backend logic and data processing using Python and SQL • Assist in writing technical specifications and user stories • Support system integrations through APIs and enterprise connectors • Conduct unit and integration testing to ensure solution accuracy • Assist with troubleshooting and production support when needed • Collaborate with global cross-functional teams and contribute to technical discussions • Maintain clear documentation and follow best development practices Requirements Requirements • 3–5 years of experience in software development (Python required) • Practical experience with LLMs, embeddings, vector databases or RAG workflows – an advantage • Experience working with SQL databases • Understanding of backend development concepts; familiarity with system integrations – advantage • Strong analytical, problem-solving and learning capabilities • Excellent communication skills and ability to work in a global environment • Fluent Hebrew (spoken and written) – must • High-level English • Ability to work on-site in Yokneam three times a week • Flexibility for occasional evening meetings

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.