Project Manager, Field Service, Applied Intelligence

About Rivian Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract. As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.

Summary Applied Intelligence is the bridge between Rivian's field operations and its digital technology teams. AI is redefining what a service operation can be, and the opportunity belongs to people who can live in both worlds at once — deep enough in the field to know how the work actually gets done, current enough with frontier AI to know what just became possible. Most roles are built for one world or the other; this team is built for both. We study the latest models, techniques, and architectures; we run time studies beside advisors and technicians; we analyze operational data at scale; and we turn what we learn into AI-native products and workflows that give the operation leverage it didn't have last quarter. We build before we hand off. Prototypes are functional, simulators stand in for the operation, and every workflow carries an eval and regression suite that proves it behaves — in shadow first, never on a customer. We are AI-first in our own work too: our admin, analysis, and project management run through the same class of tools we ask the field to trust. And we hold one constraint above the rest: everything we ship must be grounded in the measured reality of the operation — quality, performance, customer satisfaction — and must make service feel more human, not less. We automate the burdens so the people stay in the hospitality.

This Is What You’ll Do Know the operation — firsthand and at scale. Spend real time with advisors, technicians, readiness specialists, and leaders; run time studies that quantify where the hours actually go. Pair that with service, capacity, and customer-satisfaction data at scale, so every proposal is grounded in the measured reality of quality, performance, and the customer's experience. Do real research at the frontier. Track new models, techniques, architectures, and best practices as a working discipline. Evaluate what each unlocks against real service workflows — what is buildable this quarter that wasn't last quarter — and bring back conclusions, not links. Build working prototypes — and prove them. Build products, agentic workflows, and dashboards in AI-native development environments; build the simulators that exercise them; and write the eval and regression suites that hold non-deterministic systems to a standard. You hold your own quality gate. Hand off cleanly to partner teams. Translate validated workflows into what Digital Technology and AI Engineering need to build at scale: decision points, eval criteria, human-in-the-loop tiers, and the success metrics that hold in production. The handoff is where your work meets theirs; we obsess over it. Run your own work AI-first. Your admin, analysis, and project management run through the same class of tools you ask the field to trust. Your daily workflow is the demo.

This Is What You’ll Need We hire for evidence of capability, not credentials. No degree requirement at any level — not required, not preferred, not "or equivalent." A degree is welcome; its absence is not a signal. What we require instead, in any one of three forms (or a combination). Applied ingenuity. Concrete artifacts you built, shipped, or stood up — tools, systems, processes, decisions. Real, named, traceable to your own contribution. Bonus when it happened despite organizational drag, not because of it. Sequential growth in demanding, execution-driven organizations. Increasing scope — IC