Lead, AI Product Engineer, Facilities Technology

We're seeking a Lead, AI Engineer to independently design, build, and deploy AI-powered products and workflows that deliver real operational savings and improvements across Rivian's Facilities organization. This is a new kind of role — part product owner, part developer, part designer — built for the era of LLM-augmented work. You won't wait for engineering bandwidth. You'll use AI-native tools like Cursor, Gemini, Claude, and Glean to independently ship working solutions, closing the gap between an organizational problem and a working product. You own your solutions end-to-end: from identifying and scoping a costly manual process, to building the automation that replaces it, to proving the benefits after deployment. Build & Deploy

• Design, build, and deploy internal applications, agents, and multi-step automations using LLM-assisted development tools (Cursor, Gemini, Claude, Glean, etc.) targeting the highest-cost manual processes across the Facilities org, such as project reporting, cost tracking, change order management, schedule forecasting, document review, cross-functional coordination, and vendor coordination
• Connect Facilities platforms (ACC, Procore, Kahua, FOS, Databricks) via APIs and MCP integrations to create seamless, intelligent workflows that unify siloed data and eliminate duplicate work
• Stand up production-ready enterprise solutions where speed and simplicity are prioritized over engineering complexity.
• Own the Full SDLC by applying traditional product development rigor to AI-generated code. You will manage sprint cycles, define technical requirements in Jira, and oversee the end-to-end lifecycle of the tools you build.
• Engineering Excellence & Security: Act as the ultimate gatekeeper for quality. You will conduct rigorous code reviews on both human- and AI-written code, ensuring enterprise-grade security, scalability, and clean UI/UX design.
• Translate ambiguous operational problems from the Facilities team into well-structured technical architecture, using AI tools not as a crutch, but as an accelerator for rapid prototyping and deployment.
• Quantify the value of every major solution: hours saved, cost avoided, errors eliminated. If you can't measure it, rethink the approach

Mentor & Enable

• Coach Facilities team members who are developing their own AI solutions, helping them get over technical and conceptual hurdles
• Contribute to informal workshops, demos, and office hours to grow AI fluency across the Facilities organization
• Create reusable skills, plugins, playbooks, and how-to guides so that good solutions scale beyond a single use case

Partner & Translate

• Partner with cross-functional Facilities stakeholders such as project managers, construction and design leads, real estate, ops, and finance to identify the operational bottlenecks that create the most risk or opportunity for improvement.
• Maintain a deep working knowledge of the Facilities tech stack (Autodesk Construction Cloud, Revit, Kahua, and proprietary system) to build solutions that fit how people actually work
• Communicate impact to leadership in business terms — dollars, days, headcount equivalents — not just technical metrics

Required Qualifications & Skills

• 7+ years in a technical role — software development, product ownership, technical program management, or similar
• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field; OR equivalent practical, hands-on experience in lieu of a degree
• Demonstrated experience building enterprise apps with AI-assisted coding tools (Cursor, GitHub Copilot, Claude Code, OpenAI Coxed, and equivalent)
• Working knowledge of prompt and skill engineering, AI agent design and orchestration, and LLM application development
• Ability to connect systems via APIs and configure workflow automations end-to-end
• Strong UI/UX instincts — can produce functional, clean interfaces without a design team
• Excellent communication skills; equally comfortable in a whiteboard session with leadership or a working session with ops teams
• Self-directed; thrives in ambiguous environments and can quantify and communicate the business impact of technical work in terms of cost savings, time reduction, and operational efficiency

Preferred Qualifications

• Familiarity with large-scale construction, real estate, or capital programs
• Experience with enterprise AI tools like Glean or similar knowledge management platforms
• Exposure to MCP (Model Context Protocol) frameworks and multi-agent architectures
• Prior experience shipping internal tools in a non-engineering business unit
• Track record of upskilling peers or running internal training on new technologies

#LI-Hybrid