Top Artificial Intelligence Jobs in Israel

Lead and manage multiple AI-focused engineering teams while driving org-wide AI SDLC transformation. Improve developer experience with AI-driven tools and agentic workflows, set architectural vision, mentor leaders, and coordinate cross-functional delivery to ensure scalable, reliable, and observable AI-enabled platform development.

Design and build enterprise AI infrastructure, including air-gapped LLM inference clusters, RAG pipelines, chatbot interfaces, model routing, MCP/Skills ecosystems, and developer tooling. Architect AI hardware and software roadmaps, evaluate server and storage reliability, integrate local models with coding assistants, and establish secure, reproducible, maintainable operational practices. Collaborate with Product, R&D, Operations, and validation teams to optimize performance, cost, power, and data governance.

Design, architect, and scale backend platforms powering GenAI copilots and agentic decision flows. Build secure, resilient microservices and distributed systems that consolidate complex data for investigative analytics. Integrate AI models into high-performance production systems, collaborate with Data Science and Product teams, own critical components, maintain software stability, and mentor engineers. The role requires Java development, cloud-native technologies, messaging systems, relational and NoSQL databases, and experience operating high-velocity production environments.

Own the Data and AI product domain across the full lifecycle. Define product strategy, AI model integration and behavior, data analytics capabilities, and the roadmap for cybersecurity products. Partner with R&D, Sales, and customers to gather market insights, deliver AI/ML-driven features, and drive product adoption, revenue, and ongoing success.

Designs and builds reusable AI platform capabilities, production-grade agentic systems, internal AI tools, and shared AI services. Integrates emerging models and frameworks, develops end-to-end AI architectures, and operates scalable cloud-native AI systems. The role improves reliability and observability, establishes engineering standards, leads technical proofs of concept, drives adoption, collaborates with Data Science teams, and mentors engineers.

Build and ship internal AI agents, applications, intelligent workflows, and shared AI infrastructure. Own solutions end to end, from problem definition and architecture through implementation, evaluation, logging, deployment, and production support. Integrate AI with company data, APIs, and internal systems; prototype emerging technologies; collaborate directly with internal users; and develop evaluations and guardrails for reliable non-deterministic systems.

Own Sedric’s AI reference architecture across services, agents, retrieval systems, evaluation pipelines, and infrastructure. Define reusable patterns and standards, lead architecture reviews, evaluate vendors and foundation models, and shape the technology roadmap. Build production agentic systems, governance frameworks, and evaluation harnesses while partnering with Product, Engineering, customers, and executives. The role combines hands-on delivery with organization-wide technical leadership, including shipping LLM improvements and optimizing latency and reliability.

Leads the HR Technology Center of Excellence and advises senior leaders on HRIS strategy, governance, risk, controls, and technology roadmaps. Owns complex issues across Workday, payroll, and downstream systems while driving AI, analytics, process improvement, data integrity, compliance, and global operating standards. Partners with HR, IT, Finance, business leaders, and vendors to implement scalable technology-enabled transformations across North America, Europe, and Asia.

Build end-to-end customer-facing AI products and agentic systems. Design orchestration, APIs, and distributed services; implement React frontends and Python backends; deploy scalable microservices on AWS with Docker and Kubernetes; improve reliability, observability, and production performance for continuous shipping.

Lead the AI Platform development team and own architecture for a scalable, cloud-based AI cybersecurity platform. Build AI agents, skills, MCPs, plugins, and infrastructure supporting agentic development, while improving developer experience, quality, security, performance, and delivery velocity. Mentor and hire engineers, establish best practices, manage the platform roadmap, lead Agile projects, and collaborate with development and DevOps teams on high-scale, low-latency systems.

Develop AI agents to automate document processing and optimize human tasks, partnering with teams to identify automation opportunities and conducting extensive testing of AI systems.

Design, implement and optimize an NPU (Neural Network Processor) simulator in C/C++ (OOP), collaborating with architecture, algorithms, systems and hardware teams to enable efficient execution of advanced AI networks for edge devices. Analyze and improve simulator performance and accuracy across Ceva processor architectures.

Own customer-facing AI and CRM solutions, translate business needs into AI agents and automated workflows, lead implementations, coordinate with development teams, and improve internal processes using AI while managing customer relationships.

Lead end-to-end development of LLM-based applications and proprietary AI agents, build and maintain backend systems, collaborate with research and engineering, and deliver production-ready features.

Lead end-to-end product for an agentic natural-language-to-quantum-program experience: define roadmap, plugin/dev-tools integration, internal harness, eval metrics, user discovery, and cross-functional delivery sequencing.

Lead development of complex data pipelines and AI/ML systems, provide technical leadership and mentorship, design scalable architectures, write and review code, and collaborate across teams to deploy production-grade solutions involving LLMs and data engineering.

Own monitoring, evaluation, and continuous improvement of the Support bot. Define KPIs, review bot responses for quality gaps, analyze technical and business impact, collaborate with Support teams, identify trends and actionable improvements, and support the bot's evolution within Support workflows.

Lead direct sales to government ministries, defense and public safety agencies in Israel. Develop territory strategy, manage complex procurements and tenders, collaborate with engineering to map solutions, cultivate executive relationships, and drive end-to-end pipeline to exceed revenue targets.

Design and build production-grade autonomous agentic systems for supply chain problems. Architect multi-agent workflows, integrate ML/ deep learning models, evaluate agent performance, and collaborate with engineering and product teams to productize, monitor, and iterate agent pipelines.

Architect and define next-generation Spectrum-X, InfiniBand and NVLink system/software architectures. Research and run POCs, evaluate SW/HW impact across layers from algorithms to firmware, and collaborate with VLSI, system software, firmware, and research teams to deliver high-performance ML/AI interconnect solutions.

As a Product Builder, you will own product areas end-to-end, prototype user-centered features, collaborate with design and engineering, and analyze post-launch performance to drive improvements.

Lead architecture and integration of RISC-V-based compute clusters and vector engines for AI acceleration. Define ISA extensions, interconnects, memory hierarchies, scheduling, and cache utilization; collaborate with compiler, ML runtime, RTL, verification, and firmware teams; evaluate performance/power trade-offs; and specify debug, trace, and performance-monitoring features to deliver scalable, power-efficient AI SoC compute subsystems.

Design and implement high-performance kernels for AI primitives (GEMM, attention, normalization, convolution). Optimize throughput, latency, and memory hierarchy across heterogeneous compute units. Integrate kernels with Triton/PyTorch/SYCL, profile and tune with Perfetto/VTune/Tracy, prototype precision formats and stochastic rounding, and contribute micro-architecture feedback. Write reusable C++/CUDA/Triton/LLVM MLIR code.

Perform chip-level and performance verification of custom ASICs. Design end-to-end test flows and methodologies with architects to verify real-world performance. Use simulation tools and UVM environments, implement constrained-random and coverage-driven tests, and collaborate across teams and vendors to validate silicon.

The role involves developing AI agents for automating low-skill tasks, focusing on document processing and data extraction using advanced AI techniques.