What will your job look like? Design, develop, and deploy AI-driven internal tools and agentic workflows that accelerate the SDLC and reduce friction for Mobileye developers Expand the capabilities of existing platforms by embedding smart, context-aware LLM features Identify high-impact bottlenecks across the engineering organization and build zero-to-one AI solutions to solve them Architect robust orchestration layers around LLMs, focusing on practical implementations of custom system "skills," tool calling, Model Context Protocol (MCP) integrations, memory management, and Retrieval-Augmented Generation (RAG) Maintain a framework-agnostic approach, rapidly evaluating and adopting the most effective AI models, APIs, and open-source techniques as the landscape evolves All you need is: B.Sc. in Computer Science, Software Engineering, or a related technical field 4+ years of hands-on software engineering experience, with a strong focus on Python development Proven experience building and deploying production LLM applications, including agentic workflows, tool calling, and context management Nice to Have: Deep understanding of CI/CD pipelines, DevOps practices, and automated build/test systems Experience with cloud infrastructure and modern deployment architectures Familiarity with Git and GitLab, backed by practical experience in automating developer workflows
