AI Product Engineer, Technology, Facilities

Rivian•Riverdale, GA

10d•Hybrid

About The Position

Rivian is seeking an AI Product Engineer to build and deploy enterprise tools, systems, and automations that produce measurable operational savings or improvements across its Facilities organization. The role uses AI-native development tools such as Cursor, Gemini, and Claude to address practical Facilities problems, reduce manual work, and deliver quantifiable time and cost savings. The engineer will work within Facilities workflows such as construction project reporting, capital program tracking, real estate operations, and building management. The position combines rapid delivery of maintainable no-code and low-code solutions with product development rigor across the full software development lifecycle. It involves connecting Facilities data sources, gathering workflow requirements directly from stakeholders, iterating on solutions based on user feedback, and measuring their operational impact. The engineer will also build knowledge of Facilities operations, document solutions, and help colleagues adopt new tools.

Requirements

At least 4 years of experience in a technical role, such as software development, product ownership, or technical program management.
A 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 such as 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 and ability to produce functional, clean interfaces without a design team.
Strong communication skills, including the ability to work with leadership and project teams.
Self-directed approach and comfort working in ambiguous environments without an established playbook.

Nice To Haves

Familiarity with large-scale construction, real estate, or capital programs.
Experience with enterprise AI tools such as 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.
A track record of upskilling peers or running internal training on new technologies.

Responsibilities

Build and deploy internal applications, AI agents, and workflow automations to address Facilities pain points such as manual reporting, data entry, schedule tracking, and cost reconciliation, with a focus on measurable time and cost savings.
Create no-code and low-code solutions that non-technical team members can maintain when speed and simplicity are priorities.
Connect Facilities data sources, including ACC, Procore, Kahua, FOS, and Databricks, through APIs to support intelligent workflows and unify siloed information.
Manage the full software development lifecycle for tools, including sprint cycles, defining technical requirements in Jira, and overseeing end-to-end delivery.
Conduct code reviews of peer-built AI tools and enhance deployed solutions based on user feedback and changing business needs.
Build working knowledge of Facilities operations by shadowing project managers, construction teams, and operations staff to identify automation opportunities.
Understand the Facilities technology stack and identify opportunities for AI to reduce friction and 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 greatest operational ROI.
Translate operational needs into working prototypes and iterate based on user feedback to support adoption.
Track and report the impact of deployed solutions, including hours saved, errors reduced, costs avoided, and the ability to scale without adding headcount.
Upskill peers or run internal training on new technologies, if applicable to the candidate's experience.