Staff Applied AI Engineer
About this role
The Agents Group at Rocket Money is building agentic systems that transition the product from helpful surfaces into assistants capable of reliably completing work for customers. This Staff Applied AI Engineer role exists to build, evolve, and operate the Capabilities Engine, the core platform that makes agentic behavior production-ready across the company's AI experiences. Engineers in this position focus on AI as an execution layer, creating abstractions and primitives that let agents plan, use tools, recover from ambiguities, and safely execute workflows across contact methods like phone, email, and web bots.
Candidates who thrive here are comfortable navigating ambiguity and hold a high bar for quality, reliability, and trust. The ideal person understands that durable customer value relies on solid orchestration, evaluation, observability, and failure recovery rather than just simple LLM responses. Someone who enjoys building shared platform services, mentoring other engineers, and turning complex technical challenges into dependable customer-facing systems will find a strong fit.
What you will do
- Build, evolve, and operate the Capabilities Engine as a core platform for agentic product behavior.
- Design abstractions and primitives that make capabilities easy for agents and methods to discover, invoke, compose, observe, and improve.
- Partner with method owners across all contact method subagents and supporting agents to integrate methods with the Capabilities Engine.
- 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.
- Mentor and develop engineers across the Agents Group while shaping technical direction and standards.
- Document system behavior, capability contracts, tradeoffs, and operational expectations for other teams.
What you need
- Have experience shipping production software with strong engineering fundamentals.
- Possess hands-on experience or strong practical familiarity with LLM applications, agentic systems, tool calling, retrieval, workflow orchestration, or applied AI products.
- Demonstrate strong product judgment and the ability to reason from customer needs to technical architecture.
- Be comfortable working across ambiguity to identify problems, sequence work, and make necessary tradeoffs.
- Hold a high bar for quality, reliability, trust, and clear system contracts.
- Communicate clearly with engineering, product, design, data, operations, and platform partners.
Nice to have
- Experience building production LLM applications, agentic systems, workflow engines, tool-calling systems, or AI-powered product surfaces.
- Experience designing capability platforms, shared services, orchestration systems, or reusable product infrastructure.
- Experience with TypeScript, Node, GraphQL, Postgres, LLM applications, agentic systems, and workflow orchestration.
- Experience creating evaluation and observability systems for probabilistic or agentic behavior.
- Experience improving reliability, alerting, tracing, incident response, and operational quality.
Benefits
- Health, Dental & Vision Plans
- Competitive Pay
- 401k Matching
- Unlimited PTO
- Lunch daily (in-office only)
- Commuter benefits (in-office only)
Skills and tech stack
Questions candidates ask
Where is this role located?
This position is available in San Francisco, CA, Washington, D.C., New York City, NY, or as Remote (USA).
What is the salary range for the role?
The salary range is $200,000 - $270,000 per year plus bonus and benefits, with base pay varying depending on job-related knowledge, skills, and experience.
What tools and technologies are used?
The tech stack includes experience with TypeScript, Node, GraphQL, Postgres, LLM applications, agentic systems, and workflow orchestration.