Top Artificial Intelligence Jobs in Israel

Develop high-precision computer vision and deep learning algorithms for autonomous vehicle localization using surround cameras and HD maps. Design models with Transformers, GNNs, and CNNs; solve 3D geometry, scene understanding, object matching, and spatial reasoning problems; combine learned methods with optimization; analyze driving data; and take solutions from prototyping through production deployment.

Drive Applied Materials’ AI transformation across R&D by validating GenAI productivity playbook adoption, monitoring metrics and dashboards, conducting gap analysis, gathering stakeholder feedback, and identifying process or capability improvements. The role coordinates across product groups, engineers, and leaders, organizes adoption events, validates implementations against acceptance criteria, and contributes insights to the strategic direction of the productivity program.

Research emerging security risks in AI agents, including prompt injection, tool misuse, data exfiltration, memory poisoning, privilege escalation, and unsafe autonomy. Build reproducible experiments, sandboxes, detectors, graders, and regression tests across enterprise AI stacks. Translate findings into platform guardrails, red-team tests, threat intelligence, customer evidence, technical publications, conference talks, and responsible vulnerability disclosures. Collaborate with product, engineering, marketing, and external AI research organizations.

Leads global enterprise information systems, including ERP and CRM platforms, migrations, AI initiatives, vendor management, testing, change management, training, and post-deployment support. Manages hundreds of information systems, business processes, in-house developers, and the IS team while translating business needs into technical solutions and overseeing software renewals and contracts.

Own BigID’s AI Security offering end-to-end, defining its vision, strategy, roadmap, and execution. Lead initiatives spanning data loss prevention, data access governance, and securing AI/ML and GenAI data and applications. Collaborate with customers, engineering, marketing, sales, and leadership; engage design partners; support customer escalations; evangelize the product; and monitor KPIs. The role requires substantial cybersecurity product management experience and strong enterprise security expertise.

Lead and contribute to backend development for an AI datacenter orchestration platform. Build APIs, workflows, data models, and distributed services spanning compute, networking, and accelerators. Own features through implementation, testing, deployment, and production support while improving reliability, performance, observability, and CI/CD practices. Manage a software development team, participate in architecture and code reviews, and collaborate closely with customers and engineers.

Optimize and support large-scale HPC job scheduling infrastructure for EDA and GPU-accelerated AI workloads. Improve scheduler performance, utilization, throughput, and reliability across multi-site Linux environments. Develop Python and Bash automation, CI/CD and IaC tooling, LLM-based solutions, observability systems, and containerized workflows. Perform root-cause analysis, resolve infrastructure issues, maintain network licensing, and partner with customer teams to deliver technical improvements.

Lead software architecture for Ceva’s AI toolchain and NPU embedded solutions. Define performance-critical components for neural networks under power, memory, and latency constraints; collaborate across hardware, software, product, and VLSI teams; evaluate architecture and IP proposals; guide development teams; create simulators, models, and profilers; represent Ceva in customer meetings; and help shape technology roadmaps.

Build scalable infrastructure for AI agents to access repositories, pipelines, datasets, and compute. Develop CI/CD, testing, evaluation, observability, permissions, approvals, and audit controls for reliable and secure agentic workflows. Monitor agent behavior, optimize performance and costs, and support autonomous multi-agent operations. Collaborate with computational biology and engineering teams to improve AI-enabled research and development workflows.

Design and ship AI-first enablement solutions and content that teach product and business use. Rapidly prototype tools (agents, LLM workflows, no-code solutions), iterate from user feedback, deliver hands-on training, and collaborate across Product, Engineering, and client-facing teams to drive adoption and measurable impact.

Lead a small engineering team building AI-native project management solutions. Own architectural decisions and features end to end, from design and implementation through deployment and monitoring. Collaborate with product and design, integrate LLMs and AI technologies, optimize performance and scalability, and establish engineering best practices for reliable, user-centered products.

Build Cato’s AI agentic infrastructure and intelligent applications, including backend services, APIs, React frontends, databases, deployment, and production monitoring. Collaborate with AI/ML engineers, product managers, and UX designers to deliver conversational and non-conversational AI capabilities. Develop scalable, cloud-native services and drive automation, autonomous workflows, and insight generation across Cato’s security platform.

Build AI agents and automation workflows that analyze healthcare claims for billing errors, waste, fraud, and savings. Own agent harnesses, tool-calling and verification loops, experimentation systems, and production-grade LLM workflows. Develop explainable, accurate algorithms, evaluate emerging AI technologies, and guide technical direction. Requires data science, software engineering, cloud, and AI integration experience.

Leads a team of approximately five QA engineers while owning testing strategy and delivery from planning through production release. Responsibilities include manual, exploratory, API, integration, regression, and end-to-end testing; defect triage; release readiness; technical investigations; and collaboration with development, product, and automation teams. The role also advances AI-assisted QA workflows, testing standards, automation coverage, documentation, and production issue analysis.

Build Marko, a production-grade agentic marketing platform that autonomously manages advertising campaigns, creative generation, budget allocation, and performance optimization. Own specialized sub-agents, orchestration, tool integrations, approval gates, audit trails, evaluation systems, and feedback loops. Integrate major advertising platforms and collaborate with marketing leadership on campaign economics and attribution. This founding engineer role requires shipping reliable AI systems that operate at scale with real budgets.

The R&D Manager for AI Python Frameworks will lead a team to design and build foundational AI infrastructure, focusing on agent lifecycle management, observability, and developer enablement, while ensuring AI system reliability and quality across the organization.

Conduct end-to-end security research into how vendors expose customers to attack. Discover and validate attack paths using real data, evaluate security tools and data sources, shape AI risk-agent logic, build research tools, and partner with engineering to turn findings into product capabilities, detections, or published research.

Lead the engineering infrastructure for SONiC Network OS product development, enhancing CI pipelines and implementing AI tools for regression analysis. Mentor team members and drive technical direction.

Own the vision, strategy, roadmap, and end-to-end development of AI-native agreement experiences for SignNow. Lead customer discovery, product validation, prototyping, technical trade-off evaluation, launch, adoption, and continuous improvement. Partner with engineering, design, data, and go-to-market teams to build reliable, transparent agentic workflows, define success metrics, prioritize investments, and deliver measurable customer and business impact.

Lead applied research across AI, data systems, information retrieval, and large-scale storage. Design and benchmark solutions for query processing, data discovery, entity resolution, RAG, LLM evaluation, and automated software debugging. Publish research, file patents, build AI evaluation frameworks, and translate prototypes into production capabilities in collaboration with engineering and product teams.

Conduct hands-on research into frontier AI models, reasoning, agents, and multimodal systems. Design benchmarks, evaluation frameworks, and experimental pipelines; rapidly develop prototypes, run experiments, and deliver validated findings. Identify model limitations and research opportunities, translate customer challenges into measurable outcomes, and collaborate with engineering and product teams. The role requires advanced Python and PyTorch skills, strong AI research credentials, and expertise in LLMs, foundation models, benchmarking, and evaluation.

Supports technical and solution-oriented sales cycles for intelligence and security solutions. Leads discovery, solution design, proposals, demos, workshops, RFI/RFP submissions, and customer engagements. Builds relationships with technical and executive stakeholders, coordinates cross-functional teams, advises on engagement financials and risks, and influences product roadmap decisions. Designs solutions using analytics, SIGINT, cybersecurity, AI, telecommunications, big data, and cloud technologies.

Own EU enterprise sales for a subscription-based AI platform, focusing on German-speaking markets. Responsibilities include prospecting, pipeline growth, consultative selling, product demonstrations, customer relationship management, contract negotiations, market expansion, customer visits, and industry events. The role requires native or fluent German, strong B2B SaaS enterprise sales experience, strategic execution, and periodic international travel.

Lead product strategy and execution for AI-powered retail intelligence and execution products. Own discovery, prioritization, roadmaps, experimentation, launch, adoption, and measurable business outcomes. Partner with engineering, data, AI, design, sales, and customer success teams while working directly with enterprise fashion retailers. Translate complex retail, merchandising, store operations, and real-time data challenges into scalable decision-support, recommendation, workflow, and optimization products.

Annotate medical text, images, and signals for AI solutions; review results, calculate performance metrics, and report findings. Manage clinical tasks within Scrum, coordinate assignments, maintain annotation guidelines, track deliverables, assess risks, and bridge clinical and technical teams. Collaborate with engineers, data managers, and clinicians while educating colleagues on medical topics.