Staff Applied AI Engineer

Rocket Money · San Francisco, CA, Washington, D.C., New York City, NY, Remote (USA)

  • Senior
  • Full-time
  • $200,000 – $270,000
  • Posted 2026-09-24
  • Confirmed live on 25 September 2026

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Job description

ABOUT ROCKET MONEY🔮

Rocket Money’s mission is to meaningfully improve the financial prosperity of millions of people. Rocket Money offers members a unique understanding of their finances and a suite of valuable services that save them time and money – ultimately giving them a leg up on their financial journey.

ABOUT THE TEAM 🤝

Rocket Money’s mission is to meaningfully improve the financial lives of millions of people. We help customers understand their money, reduce waste, stay on top of bills and subscriptions, and take action with more confidence.

The Agents Group is building the agentic systems that let Rocket Money move from helpful product surfaces to assistants that can safely and reliably finish work for customers. The group owns the system responsible for enabling agentic capabilities and the methods that let agents interact with customers and systems across various contact methods (phone, email, web bots, etc) and autonomous workflows.

This work sits at the intersection of LLM-powered reasoning, deterministic execution systems, tool orchestration, product constraints, observability, evaluation, trust and safety, and consumer-grade product craft. The bar is not “can the agent respond?” The bar is “can the agent correctly, safely, and verifiably complete the work?”

ABOUT THE ROLE

As an Applied AI Engineer, you will help build, evolve, and operate the Capabilities Engine: the core platform that makes agentic behavior reliable, reusable, observable, and production-ready across Rocket Money’s AI-powered experiences.

You will create the primitives that capability teams need to turn ambiguous product needs into shippable technical plans, prototypes, and durable systems. You will also partner with contact-method owners across phone, email, chat, web login, ODC, and autonomous workflows to make each method more agentic and better integrated with the Capabilities Engine. That means helping agents plan, discover and invoke capabilities, recover from ambiguity, handle real-world edge cases, and complete user-facing work safely and correctly.

This role is for an engineer who is excited by—and experienced in—AI as an execution layer, not just a conversation layer. You will build systems that let agents use tools, observe outcomes, recover from failure, and earn enough trust to act on behalf of users.

You will work across product and platform boundaries, moving between architecture, implementation, debugging, evaluation, and cross-functional collaboration. Success means making the Capabilities Engine easier to extend, operate, and integrate with; improving task completion and recovery across methods; and ensuring new capabilities ship with clear contracts, tests, traces, ownership, and production-readiness expectations.

IN THIS ROLE, YOU'LL:

• Build, evolve, and operate the Capabilities Engine as a core platform for agentic product behavior.

• Design abstractions that make capabilities easy for agents and methods to discover, invoke, compose, observe, and improve.

• Partner with method owners across all contact method subagents as well as supporting agents to make each method more agentic and better integrated with the Capabilities Engine.

• Identify repeated patterns across methods and turn them into reusable capabilities, interfaces, evaluations, and operating practices.

• Provide guidance on how to monitor and optimize reliability, latency, cost, observability, and safety of capability execution in production.

• Develop practical evaluation loops for agentic behavior, including offline tests, production metrics, traces, regression suites, and qualitative review.

• Debug complex failures across model behavior, tool execution, orchestration, product constraints, and downstream systems.

• Translate ambiguous product needs into shippable technical plans, prototypes, and durable systems.

• Create the primitives capability teams need to successfully produce shippable technical plans, prototypes, and durable systems.

• Collaborate with product, design, data, platform, and operations partners to ensure capabilities are useful, understandable, and safe for real users.

• Mentor and develop engineers across the Agents Group, acting as a technical multiplier by sharing expertise, fostering a culture where others feel empowered to propose ideas and take on high-impact work, and helping shape the group's overall technical direction and standards.

• Document system behavior, capability contracts, tradeoffs, and operational expectations so other teams can build on the platform confidently.

• Drop into high-priority method work when needed to accelerate agentic behavior, unblock launches, or stabilize production issues.

• Stay curious about the frontier of applied AI engineering and help the team adopt new tools, patterns, and workflows where they make the product more dependable.

YOU MAY BE A GOOD FIT IF YOU:

• Have experience shipping production software with strong engineering fundamentals.

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