AI Engineer jobs in Israel

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.

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.

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.

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 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.

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

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

Description Accelerate Your Career in Cybersecurity! Pentera is the market leader in AI-native Security Validation, equipping enterprises with the platform to proactively test their defenses against the latest cyber attacks. Pentera proves which exposures are truly exploitable across the entire attack surface and drives remediation workflows that reduce real risk. Anchored in real-attack validation, the Pentera platform powers the full Continuous Threat Exposure Management (CTEM) cycle, from exposure discovery through prioritization, validation, and mobilization. Thousands of security teams around the world trust Pentera to close their security gaps before threat actors can exploit them. With over 350 team members and 1,300 customers in more than 60 countries, Pentera is a growing company supported by top investors such as Insight Partners, K1, and The Blackstone Group. If you want to grow your skills, make an impact, and be part of an innovative team, Pentera is the place for you. About the role: Pentera, a security company, is building an internal AI capability across the organization: agents that perform real tasks as the organization, with ROI and security assessed at every step. We are looking for a senior engineer who owns this end to end - a hands-on builder who also carries the senior function: setting the technical strategy, making the architecture calls, and being the person leadership trusts on internal AI. This is not a pure IC build role and not a pure strategy role. You will personally build the flagship systems - production agents, the context layer, the evaluation and safety stack - while also deciding what gets built, in what order, and to what standard. You will work across R&D, IT, Security, BizOps, Customer, Sales, Marketing, People, and Finance, with the AI Transformation Officer owning the business portfolio. What you'll do - strategy and senior function: • Own the technical strategy for Pentera's internal AI transformation: target architecture, model and vendor choices, build-vs-buy calls. • Shape the AI portfolio: which workflows to automate, in what sequence, with what success metrics - and push back when the wrong thing is being built. • Set and enforce the bar on ROI and security for every AI system: cost, adoption, cycle-time impact, access control, and auditability are reviewed per project, not after launch. • Act as the senior technical voice for internal AI: advise leadership, review AI initiatives across the org. • Turn one-off builds into a real internal platform: reusable patterns, shared services, and standards that AI Champions and teams adopt. • Mentor AI Champions; raise the org's practical AI level. • Manage Pentera's AI- Champions Community. • Continuously evaluate models, vendors, and frameworks, and keep Pentera agile. What you'll do - hands-on build: • Personally design, build, deploy, and own the flagship internal agents and AI workflows, from prototype through production. • Build and evolve Pentera's AI context layer: connectors, APIs, retrieval services, metadata, identity and authorization, controls, and tool interfaces. • Create safe action tools for agents and infrastructure for agents to work. • Build RAG, tool-calling, structured-output, and multi-step agentic workflows using the right model and architecture for each problem. • Own the production quality bar for what you ship: evaluation datasets and automated checks (accuracy, groundedness, task completion, safety, cost etc.) • Work directly with business owners to map processes, test with users, and drive each pilot to a clear scale-or-stop decision. Requirements • 4+ years of production software engineering, including strong Python, APIs, testing, CI/CD, data contracts, and cloud services. Applied and agentic AI is a new field - nobody has a decade of it - so we weight demonstrated ownership and depth over years: what you shipped, what you owned end to end, how deep you went. • Evidence of operating at senior scope, wherever you earned it: you have set technical direction, made architecture calls that others built on, and carried systems end to end - as a staff/lead engineer, a first AI hire, or similar. • Executive fluency: you turn ambiguous business needs into a technical plan, explain trade-offs simply to non-engineers, and say no with reasoning when needed. • Ownership mindset: you measure whether the system changed the business process, not whether the demo ran. Advantages: • Experience as a first or early AI hire, or standing up an internal AI platform or function. • Product management experience. • Experience building internal platforms or company-wide data products. We are an equal opportunity employer and we are committed to building a diverse and talented workforce. We do not discriminate on the basis of race, sex, religion, colour, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, medical condition, disability, or any other class or characteristic protected by applicable law. We welcome candidates from all backgrounds to join us!

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 We are seeking a talented AI engineer with a background in Large Language Models (LLM) and GenAI engineering. The ideal candidate will have professional experience programming in Python and a solid understanding of AI protocols and standards. In this role, you will: • Implement effective and scalable Python code. • Develop and implement GenAI applications, including Large Language Models (LLM). • Utilize GenAI engineering tools such as LangChain, RAG, and Vector Database for implementation and optimization. • Stay updated with AI protocols and standards, ensuring their correct application in projects. • Collaborate with other team members to understand requirements and develop solutions. • Analyze complex problems, identifying and defining the computational requirements to solve them. Requirements • Minimum of 5 years of experience as an AI engineer/developer • Professional programming experience in Python • Knowledge of backend frameworks such as Node.js and Django • Familiarity with APIs such as JSON and REST • Experience with GenAI engineering, implementation, and tools (e.g., LangChain, RAG, Vector Database) • Good understanding of AI protocols and standards • Frontend development experience in React or Angular is an advantage • Degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field • Excellent problem-solving and analytical skills • Experience working on global teams and collaborating via tools such as Jira, Teams, and Azure DevOps (ADO) • Advanced level of English • Valid Israeli work permit – mandatory • B.A./M.Sc. in Data Science, Computer Science, Mathematics, Statistics, etc. – an advantage Full time Job Location: Tel Aviv, Hybrid We at Deloitte believe that diversity and inclusion among our people is a critical component of our success and that is why we cultivate an organizational culture that contains and embraces diversity in all its forms.

Description VAST Data is looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI — shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work. This is a **cross-functional, company-wide role**. You won't be embedded in a single product team — instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization. This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence. "VAST's data management vision is the future of the market."- Forbes VAST Data is the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, VAST takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud. Our success has been built through intense innovation, a customer-first mentality and a team of fearless VASTronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our company’s growth and at a pivotal point in computing history. What You'll Do: - Design, build, and operate LLM-powered applications, agents, and workflows end-to-end — from prototype to production. - Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient. - Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows. - Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems. - Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities. - Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack. Requirements Engineering Foundations: - Strong Python skills- you write clean, idiomatic, well-tested code and understand the language deeply. - Hands-on experience using coding agents(Cursor, Claude Code, GitHub Copilot, or similar) to build complex software systems. You know how to delegate effectively to AI assistants and review their output critically. - Experience with multiple database paradigms- both SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis, DynamoDB, or similar). You can choose the right tool for the job. - Experience designing and integrating with third-party APIs- REST and gRPC. Comfortable building robust clients, handling auth, retries, rate limits, and schema evolution. - Production experience with Docker and Kubernetes- containerizing services, writing manifests, and debugging deployments. - Strong Linux fundamentals- confident in bash and the terminal; you can navigate, script, and troubleshoot a server without reaching for a GUI. - Experience building cloud-native tools on AWS, GCP, or Azure (compute, storage, queues, serverless, IAM). AI / LLM Expertise: - Solid understanding of what an LLM is and how it works- tokenization, attention, context windows, sampling, and the practical implications of each for system design. - Strong grasp of modern patterns for integrating LLMs into real workflows, including RAG, MCP (Model Context Protocol), vector databases, agents, tool use, and context engineering- with hands-on experience building with several of them. - Production experience implementing LLM-powered systems end-to-end, using relevant tools and frameworks (e.g. LangChain, LlamaIndex, LangGraph, Haystack, Pydantic AI, vector stores like Pinecone/Weaviate/pgvector, observability tools like LangSmith or Langfuse). - Solid foundation in core ML concepts; embeddings, evaluation, overfitting, generalization, and how classical ML relates to and differs from modern LLM-based approaches. Nice to Have: - Experience fine-tuning or distilling open-source models. - Contributions to open-source AI/ML projects. - Experience with streaming, real-time systems, or low-latency inference. - Familiarity with prompt evaluation frameworks and LLM-as-judge methodologies. - Background in distributed systems or high-scale backend engineering. What We Look For: - A builder's mindset; you ship, measure, iterate, and don't get stuck in analysis. - Comfort with ambiguity; LLM systems are non-deterministic and the field moves weekly. You navigate that with curiosity rather than frustration. - Strong communication; you can explain trade-offs to engineers, product managers, and executives alike. - Pragmatism; you know when to reach for a 200-line script and when to invest in proper infrastructure.

Description AI Specialist Engineer Location: Ra’anana, Israel About Us: DriveNets is a leader in disaggregated high-scale networking solutions for service providers and AI infrastructures. Founded in December 2015, DriveNets created a radical new way to build networks by adapting the architectural model of the cloud to telco-grade networking. This solution accelerates network deployment, improves the network’s economic model, and radically simplifies network operations. With customers including Comcast, Orange, and KDDI - over 80% of AT&T’s network traffic now runs through a disaggregated core powered by DriveNets software. DriveNets Network Cloud-AI solution, based on the same technology, was introduced to the market in 2023, providing the highest-performance Ethernet-based AI networking solution, and is already deployed by Hyperscalers, NeoClouds and Enterprises. Raising over $587 million in three funding rounds, DriveNets continues to deploy the most innovative network infrastructure and is looking for the most talented people to be part of this journey. The Role: We're looking for an AI Specialist Engineer to join our AI Enablement team. This is a high-impact role where you will build products and internal tools used across the entire company, while working with the most advanced AI tools and best practices available today. Key Responsibilities • Develop internal AI-powered products and tools used by teams across DriveNets to work faster and smarter. • Lead the evaluation, integration, and rollout of AI-powered development tools across engineering teams. • Build proof-of-concept projects and internal tooling that demonstrate the practical value of AI in real workflows. • Develop best practices, prompt engineering guidelines, and training materials for AI-assisted development. • Stay current with the rapidly evolving AI tooling landscape and advise leadership on strategic adoption. • Work hands-on with the most advanced AI development tools and shape how the company uses them. Requirements • B.Sc. or M.Sc. in Computer Science, Electrical Engineering, or a related field, graduated with Honors • AI Development Tools: Hands-on experience using AI-powered coding assistants and agentic development tools — not just familiarity, but meaningful integration into your workflow. • Communication: Ability to explain technical concepts clearly and influence adoption across teams with varying levels of AI experience. • As part of the initial stages of the recruitment process, you will be required to submit an AI project presentation based on a project built using Claude Code.

Description Bluespine is an innovative startup in the health-IT domain. Using cutting-edge technologies, we build AI-driven systems that find what's going wrong in healthcare spending: billing errors, wasteful care, and potentially fraudulent claims, which together cost the industry billions of dollars every year. We also identify concrete cost-saving opportunities for employers. Each assessment is tailored to the individual claim, taking into account the relevant provider, payer, and plan, so the results are precise and trustworthy. We're looking for a technical builder-leader who pairs strong engineering skills with a passion for AI and a drive to improve real-world processes with it. Responsibilities • Design and build AI agents and automation workflows that analyze claims at scale and find errors, waste, fraud, and savings. • Own the agent harness and the loops around it: how agents plan, call tools, verify their own work, and improve over time. • Build the systems that make experimentation with LLMs, agents, and workflows fast, measurable, and safe to ship. • Develop and validate algorithms that hold up in production, where accuracy matters and every finding has to be explainable. • Investigate, implement, and share new AI technologies and ideas, and set the technical direction for how we use them. Requirements • 5+ years of data science/analysis experience. • 2+ years of software engineering experience (Python, Node.js, Go, or similar). • Hands-on experience building or integrating AI tools, APIs, or agents. • Familiarity with LLM-based patterns such as agentic workflows, harness and loop engineering, and production-level prompt engineering. • Experience with cloud platforms such as AWS, Google Cloud, or Azure. • Strong communication, interpersonal, and problem-solving skills. Advantages • Background in healthcare data or fraud investigations. • Prior experience in health insurance tech or medical coding/billing. • Degree in computer science or equivalent.

Description Popai is on a mission to transform the millions of conversations that happen between care teams and patients every day. We’re building the AI platform that turns every patient interaction into action - helping care teams understand what patients need, close gaps in care, and reach the people who need them most. Our goal is simple but ambitious: make he As an AI Engineer at Popai, you will design, build, and deploy intelligent systems that power our core product. You will work across the entire lifecycle—from building robust data pipelines for medical records and audio data to operationalizing cutting-edge LLMs and agentic workflows in production. What You'll Do • Build AI & Data Pipelines: Design, build, and maintain data and AI pipelines that ingest, process, and analyze large-scale healthcare data (including medical records, audio signals, and system traffic). • Develop Intelligent Systems: Build systems that extract structured entities, definitions, and actionable insights from complex unstructured data. • Deploy AI Agents: Operationalize and integrate AI agents using LLMs, open-weight models, and specialized tools into production systems to automate reasoning and care workflows. • Optimize Performance: Optimize model performance, inference pipelines, and latency to ensure high scalability and efficiency. • Ensure Data Quality & Observability: Design reliable data workflows with built-in quality checks, consistency, and monitoring across all pipeline stages. • R&D & Innovation: Experiment with emerging AI frameworks, model architectures, and agentic workflows to continuously elevate the platform's intelligence. Requirements What We're Looking For • Experience: 6+ years of hands-on experience as a Software Engineer, AI Engineer, or Data Engineer. • Scalability & Systems: Proven track record of working on high-scale, distributed systems with a focus on performance optimization and resilience. • Data Infrastructure: Solid understanding of data processing and storage technologies (e.g., PostgreSQL, BigQuery, Snowflake, Spark, Kafka). • AI & LLM Deployment: Practical experience integrating, serving, or fine-tuning LLMs and smaller specialized models (API-based or open-weight). • Cloud & DevOps: Proficiency with cloud platforms (AWS, GCP, or Azure) and containerized setups (Docker, Kubernetes). Nice to Have • Experience with LLM serving optimizations, quantization, prompt engineering, or agent orchestration frameworks (e.g., LangChain, LangGraph). • Familiarity with audio/speech processing or medical record data systems. • Experience designing event-driven, streaming architectures. • Background in real-time inference or low-latency AI applications.

Description We Are KPMG Israel. KPMG Israel is more than a professional services firm, we are a community of people driven by impact. As part of a leading global network, we partner with the most influential organizations to drive large-scale business and technology transformation, combining strategic thinking, innovation, and advanced technologies. Guided by integrity, excellence, and forward thinking, we help organizations navigate complexity and create real change. Our people are at the center, with space to lead, experiment, and grow in a dynamic and collaborative environment that connects personal development with meaningful impact on the future of business and society. We are seeking an experienced Generative AI Engineer to join our AI squad at KPMG. This is a unique opportunity to wear multiple hats - serving as both a developer of cutting-edge GenAI solutions and an advisory expert helping organizations transform their AI capabilities. You'll build end-to-end GenAI projects from conception to production while staying at the forefront of this rapidly evolving field. Key Responsibilities GenAI Development & Implementation • End-to-End Development: Build GenAI solutions from POC through production deployment, handling all backend development responsibilities • Client Engagement: Participate in technical discussions with clients, gather requirements, and help translate business visions into feasible technical solutions through presentations and consultations • Backend Development: Design and implement production-grade microservices architectures for GenAI applications using Python • Cloud Implementation: Deploy and manage GenAI solutions across GCP, Azure, and AWS platforms, leveraging cloud-native AI services • Cross-functional Collaboration: Work closely with project managers, full-stack developers, and Power Automate teams to deliver complete solutions • System Evaluation: Assess and optimize production-grade GenAI systems for performance, scalability, and reliability Continuous Learning & Innovation • Technology Scouting: Continuously explore and evaluate new GenAI models, frameworks, and techniques as they emerge • Best Practices Development: Establish and refine methodologies for GenAI solution development and deployment Requirements Technical Expertise: • Programming: Advanced proficiency in Python for backend development and AI applications • GenAI Mastery: Deep understanding of large language models (LLMs) and experience with major model APIs (OpenAI, Anthropic, Google, etc.) • Multi-Agent Systems: Expertise in designing and implementing GenAI multi-agent architectures • Prompt Engineering: Advanced skills in prompt design, optimization, and engineering techniques • Cloud Platforms: • Required: Hands-on experience with AI services in at least one major cloud platform (GCP, Azure, or AWS) • Advantage: Experience across multiple cloud platforms (AI Search, Vertex AI, SageMaker, etc.) • Development Frameworks: Experience with GenAI frameworks like LangChain and cloud-based retrieval services • Software Engineering: Strong background in microservices architecture, API development, and production system design • AI/ML Fundamentals: Solid understanding of deep learning principles and GenAI techniques • Containerization (Advantage): Experience with Docker and Kubernetes for deployment and orchestration • OCR Technologies (Advantage): Experience with Optical Character Recognition systems and document processing • Data Pipelines (Advantage): Experience building and maintaining data processing pipelines Professional Experience • Mid+ Level Experience: 2+ years in AI/ML development with significant GenAI project experience • Production Systems: Proven track record of deploying and maintaining AI solutions in production environments • Client-Facing Experience: Comfortable with technical presentations and requirement gathering sessions Education & Background • Preferred: Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related technical field • Alternative: Demonstrated industrial experience in developing deep learning and GenAI solutions (degree not required with strong portfolio) Soft Skills • Problem-Solving: Excellent analytical and creative problem-solving abilities • Communication: Strong technical communication skills for both technical and non-technical audiences • Collaboration: Proven ability to work effectively in cross-functional teams • Adaptability: Thrives in fast-paced environments and eager to learn emerging technologies • Consulting Mindset: Ability to understand client needs and provide strategic technical guidance What We Offer • Opportunity to work on cutting-edge GenAI projects across diverse industries • Dual role combining hands-on development with strategic consulting • Access to latest AI technologies and cloud platforms • Collaborative environment with cross-functional teams • Professional development in a rapidly evolving field Diversity & Inclusion This position is open to all qualified candidates. We support diversity and view it as a strength that enhances our ability to develop, learn, and innovate. We advocate for inclusion and empower people of all backgrounds to contribute their unique perspectives.