AI Product Engineer: Facilities Automation & ROI

Rivian Automotive

Atlanta (GA)

On-site

USD 99,000 - 130,000

Full time

3 days ago

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Benefits offered by this job

Comprehensive benefits

401(k) plan

Equity opportunities

Job summary

Rivian Automotive is seeking an AI Product Engineer to build and ship enterprise tools and automations that lower costs and save time in Rivian's Facilities organization. You’ll apply AI-native development tools like Cursor, Gemini, and Claude to turn real facilities problems into practical solutions.

You’ll own the full SDLC in Jira, integrate data sources (ACC, Procore, Kahua, FOS, Databricks), and design scalable automation with strong UI/UX.

Qualifications

4+ 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 with AI-assisted coding tools (Cursor, Codex, Claude Code, or equivalent)
Working knowledge of prompt engineering, AI agent design, and LLM application development
Strong foundational knowledge of Agile methodologies, version control (Git), code reviews, and secure deployment pipelines.
Strong UI/UX instincts — can produce functional, clean interfaces without a design team
Strong communication skills; equally comfortable in a whiteboard session with leadership or a working session with project teams
Self-directed; thrives in ambiguous environments where the playbook doesn’t exist yet

Responsibilities

Build internal applications, AI agents, and workflow automations using LLM-assisted development tools (Cursor, Gemini, Claude, Glean, etc.) targeting specific Facilities pain points — manual reporting, data entry, schedule tracking, cost reconciliation — with a focus on quantifiable time and cost savings
Stand up no-code and low-code solutions, maintainable by non-technical team members where speed and simplicity are prioritized over engineering complexity
Connect Facilities data sources (ACC, Procore, Kahua, FOS, Databricks) via APIs to support intelligent workflows that unify siloed information
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.
Conduct code reviews on peer-built AI tools and own enhancement of deployed solutions based on user feedback and evolving business needs
Rapidly build working knowledge of Facilities operations — how capital projects are planned, budgeted, tracked, and delivered — by shadowing project managers, construction teams, and operations staff to find automation opportunities that aren't on anyone's roadmap yet
Understand the Facilities tech stack well enough to identify where AI can eliminate friction and reduce costs
Document solutions, create reusable templates, and contribute to internal playbooks and how-to guides
Partner with Facilities stakeholders to understand workflows, quantify inefficiencies, and prioritize automations with the highest operational ROI
Translate operational needs into working prototypes and iterate based on user feedback until adoption sticks
Help track and report the impact of deployed solutions — hours saved, errors reduced, costs avoided, scaling without new headcount