AI Engineer jobs in Herzliya

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

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 CodeValue is looking for a hands-on Senior AI Engineer with real-world experience building and deploying LLM-based and Agentic Systems to production. You will be responsible for taking AI solutions from concept to reliable, scalable production systems, working across AI, backend, cloud, and infrastructure. Responsibilities • Design, develop, and deploy LLM-based and Agentic Systems for production environments. • Take AI/Agentic solutions from PoC and concept stages to stable, scalable, and reliable production systems. • Develop backend services and AI solutions using Python. • Work hands-on with agentic frameworks such as LangGraph, CrewAI, or similar/custom frameworks. • Deploy and operate AI systems in cloud environments. • Troubleshoot complex system issues and improve observability, reliability, and performance. • Collaborate with development, DevOps, security, and other technical teams. Requirements • · 5+ years of hands-on experience in product-based tech companies, with a focus on AI/ML systems. • · Proven track record in designing and implementing GenAI-powered solutions using LLMs and transformer-based architectures. • · Deep understanding of prompt engineering, RAG (Retrieval-Augmented Generation), fine-tuning, and LLM-based workflows. • · Strong experience with Azure Cognitive Services. • · Proficiency in Python or other relevant languages (e.g., TypeScript, Go), including use of AI/ML frameworks (e.g., LangChain, Hugging Face, PyTorch). • · Familiarity with containerized environments and orchestration tools (e.g., Docker, Kubernetes). • · Comfortable working with multi-cloud environments (Azure, AWS, or GCP). • · Experience with Agile/Scrum development methodologies. • · Strong communication skills and fluency in English (spoken and written). • • Preferred Qualifications/ Skills • · Experience with building high-performance distributed systems. • · Familiarity with agentic frameworks for multi-step reasoning or workflow automation. • · Exposure to AI model governance, data compliance, and MLOps pipelines. • · Background in Computer Science or related technical degree.