Top Artificial Intelligence Jobs in Jerusalem

The engineer will optimize AI libraries and components for unique hardware, focusing on performance improvements in AI models and kernels.

The AI Compiler Engineer will develop the AI graph compiler and work on the software stack to optimize AI models for unique hardware architecture. Responsibilities include enhancing performance for AI models and contributing to related components in the software stack.

Lead and govern AI-enabled business transformation initiatives, translating strategy into execution plans, KPIs, ROI models, and cross-functional adoption. Manage prioritization, dependencies, risk tracking, stakeholder alignment, and senior leadership communications to ensure measurable business impact.

Hands-on Growth Marketing Manager responsible for full-funnel B2B demand generation. Build and run paid acquisition, ABM and field marketing, optimize funnels and landing pages, leverage AI/LLM agents to automate tasks, partner with Sales, and measure MQLs, CPL, CAC and pipeline contribution to drive qualified pipeline and campaign performance.

Lead adoption of agentic AI coding tools across engineering, build internal context and tooling (agents, MCP integrations, prompts), run enablement and playbooks, measure impact on delivery, and set security and usage guardrails to scale AI-powered engineering.

Lead strategy, roadmap, and delivery of generative AI products (LLM copilots, knowledge assistants, document intelligence) for supply chain. Drive data readiness, governance, evaluation, cost management, and value tracking. Build practice, mentor teams, and align cross-functional partners to scale production LLM solutions with Responsible AI controls and measurable business outcomes.

Lead strategy, roadmap, and delivery of agentic AI products for supply chain. Design multi-agent systems, ensure data readiness, establish Responsible AI governance, build practice and playbooks, mentor teams, prioritize by ROI, and drive adoption and measurable business value across enterprise supply chain operations.

Own and evolve ClickHouse's Python connector and SDK ecosystem; build enterprise-grade integrations with orchestration and transformation tools; design AI/LLM integration patterns for RAG, vector search, and feature pipelines; engage with open-source community; collaborate with Product and Cloud teams to prioritize and deliver robust, high-performance connectors.

Lead and deliver AI-driven engineering initiatives from scoping and architecture through hands-on execution. Drive adoption of AI tooling and practices across Dev and DevOps, identify opportunities to improve velocity, incident response, cost efficiency and reliability, align stakeholders, unblock dependencies, and evaluate emerging AI tools for production-grade solutions.

Lead identification, design, and implementation of scalable generative-AI solutions. Evaluate models and tools, build prompts, RAG pipelines and AI agents, integrate workflows with systems, run projects from ideation to rollout, and guide organizational AI adoption.

Develop and maintain an AI-driven pipeline to auto-generate, process, and publish real-life and digital quests. Integrate AI frameworks, design scalable automation workflows, analyze user data to improve generation quality, build API integrations, participate in architecture and documentation, test with pytest/unittest, and collaborate with cross-functional teams to validate LLM outputs against real-world data.

Lead and build a Quality function for an AI-native R&D org: own in-Machine quality gates, production verification, monitoring-as-code, evals of LLM/agent output, set quality metrics, and manage a ~9-person team to ensure reliability and reduced regressions.

The role involves evaluating AI outputs, generating original content, reviewing texts, and ensuring cultural relevance. Candidates should have native fluency in Hebrew and a strong command of English, with attention to detail and the ability to follow guidelines.