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
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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
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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
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Stand up production-ready enterprise solutions where speed and simplicity are prioritized over engineering complexity.
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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.
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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.
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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.
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Quantify the value of every major solution: hours saved, cost avoided, errors eliminated. If you can't measure it, rethink the approach
Mentor & Enable
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Coach Facilities team members who are developing their own AI solutions, helping them get over technical and conceptual hurdles
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Contribute to informal workshops, demos, and office hours to grow AI fluency across the Facilities organization
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Create reusable skills, plugins, playbooks, and how-to guides so that good solutions scale beyond a single use case
Partner & Translate
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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.
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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
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Communicate impact to leadership in business terms — dollars, days, headcount equivalents — not just technical metrics
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7+ years in a technical role — software development, product ownership, technical program management, or similar
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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
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Demonstrated experience building enterprise apps with AI-assisted coding tools (Cursor, GitHub Copilot, Claude Code, OpenAI Coxed, and equivalent)
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Working knowledge of prompt and skill engineering, AI agent design and orchestration, and LLM application development
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Ability to connect systems via APIs and configure workflow automations end-to-end
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Strong UI/UX instincts — can produce functional, clean interfaces without a design team
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Excellent communication skills; equally comfortable in a whiteboard session with leadership or a working session with ops teams
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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
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Familiarity with large-scale construction, real estate, or capital programs
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Experience with enterprise AI tools like Glean or similar knowledge management platforms
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Exposure to MCP (Model Context Protocol) frameworks and multi-agent architectures
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Prior experience shipping internal tools in a non-engineering business unit
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Track record of upskilling peers or running internal training on new technologies
#LI-Hybrid
