Top Artificial Intelligence Jobs in Israel

Partner with Customer Success to identify and deliver AI use cases: build, test, and operationalize AI agents, automations, and workflows integrated with CS systems (Zendesk, Slack, Notion, CRM). Drive adoption through enablement, define KPIs, measure impact, and translate field intelligence into product and process improvements to move CS from reactive support to proactive operational intelligence.

Lead a team of engineers to design and implement scalable systems for AI-driven experiences, ensuring integration across the platform, while fostering a culture of innovation and growth.

Design and build AI-driven developer workflows and agents within Datadog, from prototyping to production. Implement prompt engineering, evals, and integrations with developer tools and extensions. Collaborate with product teams to productionize LLM-based features (e.g., debugging agents), iterate with users, and follow LLM/agent research to improve developer productivity.

The role involves managing the AI platform roadmap, defining reusable AI capabilities, collaborating with engineering, and shaping AI standards within the product ecosystem.

The AI Engineer is responsible for designing, implementing, and deploying AI systems and applications, focusing on machine learning models and large language models (LLMs).

Lead the AI-first product strategy for monday service, owning discovery, roadmap, and execution. Collaborate with engineering, design, data science, and GTM teams to build AI/ML/LLM-powered service workflows, validate ideas via experiments and research, and represent Service AI internally and externally.

Design, build, and ship production LLM agents and agentic features end-to-end. Prototype and productionize state-of-the-art agentic techniques, evaluate agent quality offline and online, and partner with product and design to deliver AI features.

Design, build, and maintain backend infrastructure and microservices enabling AI-driven features. Integrate AI models, develop APIs and data pipelines, ensure performance and resilience, drive engineering excellence, and mentor other backend developers.

Lead the transition to a self-hosted LLM ecosystem, optimizing model inference, developing agentic workflows, and executing fine-tuning strategies for chatbot enhancement.

The AI System Architect leads and defines enterprise AI architecture, oversees integration strategies, manages platforms, and ensures governance compliance, shaping the AI roadmap and managing technical standards.

The role involves architecting AI verification methodologies, developing AI tools for formal verification, and collaborating with CAD teams to enhance automation workflows.

Own go-to-market for monday CRM AI: develop and package AI use cases, create high-cadence content, activate sales field with plays and demos, influence product roadmap, build GTM partnerships, and drive AI adoption and revenue.

Lead a 0-to-1 product area building AI trust for autonomous agents: define strategy, design trust and governance surfaces, run research and experiments, work closely with enterprise customers, and drive cross-functional execution to enable safe, transparent, scalable agent adoption.

As Senior Corporate Counsel, you will provide legal advice on various matters, draft and negotiate agreements, and support different teams across NVIDIA's Israeli operations.

The Senior Customer Program Manager will oversee program execution for technical and operational initiatives, ensuring alignment with customer needs and driving collaboration across global teams.

Lead the developer-focused AI product vision and roadmap, build agentic developer tools and infrastructure, drive adoption through user research and metrics, coordinate cross-organizational initiatives, and ship AI-powered developer workflows and integrations while measuring quality and impact.

Design and build AI-native systems and agent orchestration from 0→1. Own model quality lifecycle, evaluation frameworks, production monitoring, and continuous improvement. Rapidly experiment with models, prompts, and architectures, and collaborate with product and engineering to deploy reliable, scalable AI features.

Lead the global AI go-to-market motion: create sales playbooks, enable sellers and marketers, present AI capabilities to customers, drive adoption and pipeline, and align Product, Enablement, and Marketing around AI positioning.

Design, build, and deploy LLM-based developer tools and agentic systems. Lead end-to-end AI R&D, implement prompt engineering, RAG and multi-agent pipelines, measure model performance, and define AI/ML best practices with cross-functional partners.

Lead development of internal AI-driven developer tools and agents, owning design through deployment. Collaborate with Product and R&D to prototype and build features that improve developer velocity, code quality, and reliability, while mentoring engineers and monitoring productivity metrics for continual optimization.

Lead strategy and execution for autonomous agents across monday.com's platform: define agent roadmap and UX, architect planning/memory/tool-use, establish evaluation frameworks for performance and reliability, collaborate with engineering to balance latency and cost, and drive productization of AI agent features at scale.

Lead transformation of BI into an AI-driven data strategy: design and own a governed semantic knowledge layer, implement GenAI solutions and LLM-powered workflows, orchestrate AI agents, ensure data quality, governance, and self-service insights across the company.

Lead design and development of scalable AI infrastructure and full-stack products. Integrate AI agents and workflows, own systems from data ingestion to user-facing experiences, solve complex engineering challenges, collaborate with cross-functional teams, and mentor junior engineers.

Design and build production AI products, agents, and workflows for GTM teams. Own projects end-to-end from discovery to deployment, evaluate emerging AI technologies, develop scalable LLM-based systems and orchestration, partner cross-functionally, and establish engineering best practices to drive measurable business impact.

As a Senior Data Scientist, you will build NLP and ML models, lead projects, and drive data science solutions across B2B and B2C domains at Lightricks.