Jerusalem
Temporary Full-time
About us:
Mobileye is a global leader in Physical AI, developing computer vision, software, and hardware to power autonomous driving solutions and humanoid robots. Our mission is to bring autonomy into the real world by building intelligent technologies that are designed to expand accessibility and enhance everyday life, from advanced driver assistance systems (ADAS) and autonomous driving to robotics and humanoids.
Built on decades of automotive innovation and industrial-scale AI expertise, Mobileye technologies power more than 230 million vehicles worldwide. With teams around the world, we continue to innovate at the forefront of autonomous systems, advancing the next generation of Physical AI for the real world.
About the team:
Mobileye is looking for an Applied AI Engineer to join the MECI Interfaces team within the Software Engineering organization. The MECI Group enables Mobileye’s algorithmic development flow by building scalable CI, build, test, and AI-driven tooling that supports the full development lifecycle. Our platforms allow Mobileye to scale efficiently and increase development velocity, while maintaining high standards of reliability, collaboration, and developer well-being. As an Applied AI Engineer, you will be at the forefront of integrating Large Language Models (LLMs) and agentic workflows into our internal platforms. Your primary goal will be to solve complex problems across the Software Development Life Cycle (SDLC) by building intuitive, AI-powered tools that directly support our developers and internal users. This role offers the unique opportunity to both expand the intelligence of our existing developer tools and architect entirely new workflows from the ground up in a highly technical, fast-paced environment.
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.
