Implement enterprise AI use cases from discovery to production by deploying productivity tools, building agents and integrations, and ensuring secure, reliable adoption across business and IT teams.
AI Implementer
๐ Description
- Lead evaluation, deployment, licensing, access provisioning, onboarding, and adoption of enterprise AI development and productivity tools.
- Design, build, and deploy AI agents, assistants, and automations for IT and business units.
- Develop and maintain MCP integrations and connect AI solutions to enterprise systems, SaaS applications, and APIs.
- Extend the corporate chatbot with self-service automations and knowledge sources.
- Track AI usage, costs, and KPIs, including ticket deflection and automation runs.
- Apply security and governance controls, support users, document tools, and evaluate new technologies through proofs of concept.
๐ ๏ธ Requirements
- 3+ years of hands-on experience in DevOps, automation, systems engineering, or software development.
- Strong scripting or programming skills.
- Hands-on experience with LLMs or GenAI, including prompt engineering, RAG, agents, and function or tool calling.
- Experience with REST APIs, JSON, webhooks, and SaaS or enterprise system integrations.
- Working knowledge of Docker or Kubernetes, CI/CD, and Git.
- Strong communication skills and ability to explain AI to non-technical stakeholders.
- Fluent Hebrew and English.
- Nice to have: MCP experience, identity and access or security knowledge, and familiarity with AI platforms such as Bedrock, Azure OpenAI, Copilot Studio, Open WebUI, LangChain, or LangGraph.
Full job description
The IT AI team is responsible for rolling out enterprise AI tools for development and productivity across Mobileye; including AI coding assistants, enterprise copilots and agents. The team builds and runs AI solutions that turn business needs into practical, secure and reliable tools.
We're looking for a hands-on AI Implementer to take AI use cases from idea to production. You'll work with business and IT stakeholders to find automation opportunities. You'll then build agents, MCP integrations and workflows, and make sure they run securely and reliably and are actually used.
What will your job look like:
All you need is:
Nice to have:
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