Top Artificial Intelligence Jobs in Israel

Build the Agentic SDLC using autonomous AI agents to automate and improve software delivery from ideation through production monitoring. Develop scalable full-stack applications, architecture, developer experience workflows, and release-cycle automation. Collaborate across R&D while owning high-impact projects end to end. The role uses Node.js, Golang, TypeScript, React, AWS, Kubernetes, Redis, MySQL, and Elasticsearch, with DevOps and CI/CD experience preferred.

Build and own production AI systems end to end, including agent behaviors, model-driven architectures, evaluation, deployment, and monitoring. Develop AI agents for automated financial reconciliation and close management while solving technical, data, and product challenges. Partner with accounting and finance experts and contribute to scalable data pipelines, autonomous workflows, and finance-grade AI accuracy.

Leads Aitech’s AI roadmap and organization-wide enablement program. Identifies and implements high-impact AI use cases, builds agents, copilots, automations, and knowledge assistants, and scales solutions from proof of concept to production. Partners with technical and business teams on secure infrastructure, governance, responsible AI, adoption, and organizational change. Measures business impact through productivity, efficiency, quality, decision-making, and ROI improvements.

Develop and deploy real-time AI models for autonomous driving, including vision-language, motion prediction, imitation learning, and reinforcement learning systems. Bridge cloud-scale training with efficient edge deployment through compression, quantization, and inference optimization. Translate research into production systems, collaborate on autonomy architecture and long-horizon planning, and evaluate state-of-the-art AI techniques for safety-critical automotive applications.

Own the HR AI roadmap and governed HR data model across HiBob, Snowflake, and downstream systems. Build and launch AI agents, automations, and self-service data products; define data governance, access controls, privacy safeguards, and success metrics. Serve as HR’s AI advisor, enable nontechnical builders, and partner with IT and BizApps on architecture, security, and technical requirements.

This role involves engaging with customers post-sale to implement AI solutions, configure workflows, deploy systems, and ensure customer success throughout the lifecycle.

Analyze AI agents and product features to identify performance patterns, edge cases, and improvement opportunities. Define AI performance metrics, build scalable analysis tools and pipelines, and translate findings into prioritized product direction. Partner with product, engineering, customers, and field teams to improve customer value and growth. The role also evaluates AI and ML product quality, supports cross-functional decisions, and may mentor analysts or establish analytical standards.

Own Olly, Coralogix’s flagship AI product, from concept through launch. Partner closely with engineering on architecture and execution, use AI workflows to prototype and streamline product development, translate customer needs into impactful capabilities, and track business metrics. The role requires technical fluency, strong product ownership, experience with complex B2B SaaS or infrastructure products, and comfort in ambiguous startup environments.

Own AI product initiatives from discovery through launch and iteration. Design and ship agentic workflows that automate property management operations with human oversight. Partner with engineering, design, operations, and business teams; define metrics, run experiments, and use feedback to guide product direction. The role requires production AI product experience, generative AI expertise, strong AI UX judgment, zero-to-one startup experience, and hands-on use of AI tools.

Drive AI and business transformation initiatives from strategy through execution. Manage governance, prioritization, workstreams, dependencies, risks, KPIs, ROI models, and stakeholder accountability across global teams. Partner with business, product, AI, and IBT stakeholders to implement adoption frameworks, build transformation processes, resolve blockers, and communicate progress to senior leadership.

Own the end-to-end architecture and technical direction of production AI/ML systems for cellular RAN networks. Lead model selection, agent orchestration, RAG, data pipelines, evaluation, deployment, monitoring, and lifecycle management. Prototype critical components, establish engineering standards, mentor engineers, and collaborate with RAN, PHY, software, product, and customer-facing teams. Apply LLMs, classical machine learning, anomaly detection, and time-series analysis to network operations and wireless challenges.

Lead and grow a multidisciplinary AI engineering team, define technical strategy and roadmaps, and deliver production ML and LLM solutions across RAN products. Own architecture, evaluation, scalability, reliability, monitoring, and model lifecycle practices. Partner with Product, Systems, R&D, and telecom domain experts to identify AI opportunities, achieve measurable business impact, support customer trials, and manage recruitment, mentoring, performance, and delivery.

Build and ship end-to-end AI-driven applications and features, handling UI, light DevOps, data cleanup, and full-stack troubleshooting. Translate evolving business requirements into practical technical solutions, use agentic coding workflows, and collaborate with product and internal stakeholders. The role requires independent execution, strong communication, product judgment, and comfort with ambiguity. Experience with LLM applications, evaluations, and RAG is advantageous.

Leads Data Science, Network Research, and Asset Classification teams developing highly accurate cyber-physical system visibility solutions. Oversees AI/ML scaling, feature engineering, industrial and medical protocol parsing, data fusion, and passive and active data collection. Collaborates with product and R&D teams to support asset discovery, classification, risk management, segmentation, and threat detection across OT, ICS, and IoMT environments.

Build and deploy production-grade LLM and agentic systems using Python. Responsibilities include developing backend services, transitioning AI solutions from proof of concept to scalable production, deploying in cloud environments, and improving system observability, reliability, performance, and security. The role requires hands-on experience with agentic frameworks such as LangGraph or CrewAI and collaboration with engineering, DevOps, and security teams.

The Senior Backend Engineer will design and implement AI-driven backend services, ensuring high performance and reliability while collaborating with multidisciplinary teams.

Lead the end-to-end design vision for monday Agents, define new human-agent interaction paradigms, ship high-quality Desktop and Mobile experiences, raise design craft, mentor designers, and collaborate with Product, Engineering, Data Science, and Research to validate and iterate agentic features.

Design and deliver production-ready enterprise AI architectures, translating customer business, data, security, and technical requirements into scalable solutions. Lead discovery, architecture workshops, integrations, model selection, RAG and agentic workflows, evaluation, observability, governance, and security. Provide technical leadership through implementation and production readiness, while building prototypes, validating decisions through code, and troubleshooting complex systems.

Lead customer deployments of Solid from kickoff through production, designing solution architectures and developing Python integrations and tooling. Build and validate semantic models, connect AI workflows and enterprise systems, troubleshoot technical issues, and serve as the primary technical customer contact. Manage multiple workstreams, collaborate with BI, IT, Data, Security, and business teams, and translate customer feedback into product requirements for R&D.

Design, deploy, and operate enterprise Voice AI, Text AI, conversational workflow, and conversation-analysis solutions. Translate customer requirements into technical implementations, integrate APIs, CRMs, telephony systems, databases, and knowledge bases, and configure prompts, workflows, models, and tools. Monitor production agents, troubleshoot integrations, optimize performance, and support SaaS customers while coordinating with Product, R&D, Sales, and Customer Success.

Own the AI cost visibility product end-to-end, building Go backend services, APIs, and TypeScript/React interfaces. Translate cloud AI spend data into clear FinOps experiences, use AI throughout development, and ensure reliability, monitoring, and measurable customer impact. Define product direction, work through ambiguity, contribute to architecture and design reviews, mentor engineers, and deliver scalable multi-tenant SaaS capabilities across public cloud platforms.

Own product positioning, messaging, launches, sales enablement, case studies, and client marketing for an AI-powered mobile gaming user-acquisition platform. The role translates complex technology into compelling buyer language, builds bottom-of-funnel proof, supports sales, develops customer community programs, and feeds market insight back to product and founders. Candidates must have product marketing experience in B2B SaaS, product launch experience, exceptional writing skills, and an AI-native workflow using Claude Code or a comparable agentic tool.

Explores and prototypes AI, agent, real-time transport, memory, and infrastructure technologies. Runs technical spikes, evaluates unfamiliar codebases, designs benchmarks, measures latency and cost, and produces evidence-based build-versus-adopt recommendations. Hands findings to production teams and tracks the evolving AI tooling landscape.

Designs scalable, high-performance LLM inference architectures across GPU clusters. Responsibilities include optimizing latency, throughput, cost, memory orchestration, scheduling, networking, KV caching, parallel execution, and dynamic batching. The role collaborates across software, hardware, compiler, model, and networking teams; evaluates emerging technologies; translates architecture into production systems; and authors technical specifications and documentation.

Lead end-to-end product design for an AI voice-agent platform: research, explore, and ship agent experiences. Bridge voice conversations and UI for configuration, review, handoff, and reporting. Use coding agents to move designs to production, partner with Product and Engineering, validate through research and metrics, and raise design craft across the team.