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AI Product Engineer, Technology, Facilities

Job in Atlanta, Fulton County, Georgia, 30383, USA
Listing for: Rivian Automotive
Full Time position
Listed on 2026-10-18
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Engineer, Full Stack Developer
Salary/Wage Range or Industry Benchmark: 99000 - 130000 USD Yearly USD 99000.00 130000.00 YEAR
Job Description & How to Apply Below
About Us

Rivian and Volkswagen Group Technologies is a joint venture between two industry leaders with a clear vision for automotive’s next chapter. From operating systems to zonal controllers to cloud and connectivity solutions, we’re addressing the challenges of electric vehicles through technology that will set the standards for software-defined vehicles around the world.

The road to the future is uncharted. By combining our expertise across connectivity, AI, security and more, we’ll map a new way forward. Working together, we’ll create a future that’s more connected, more intelligent, more sustainable for everyone.

Role Summary

We're looking for an AI Product Engineer to build and ship enterprise tools, systems and automations that drive measurable operational savings or improvements across Rivian's Facilities organization. You'll use AI-native development tools like Cursor, Gemini, and Claude to turn real Facilities problems into working solutions that save time, reduce cost, and eliminate manual overhead. You'll embed directly into Facilities workflows — construction project reporting, capital program tracking, real estate operations, building management — and build automations that have a tangible dollar-and-cents impact.

Responsibilities

Build & Deploy
  • 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

Learn the Business
  • 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

Collaborate & Deliver Value
  • 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

Qualifications

Required Qualifications & Skills
  • 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),…

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