Note: The job is a remote job and is open to candidates in USA. Rocket Money helps customers understand their finances, reduce waste, stay on top of bills and subscriptions, and take action with more confidence. The Staff Applied AI Engineer will build, evolve, and operate the Capabilities Engine, creating reliable, reusable, observable, and production-ready systems for agentic behavior. The role also involves integrating contact methods, improving agent evaluation and recovery, debugging complex failures, and mentoring engineers across the Agents Group.
Responsibilities
- 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
Skills
- * Have experience shipping production software with strong engineering fundamentals
- * Are excited by AI as an execution layer. You understand that durable customer value comes from orchestration, tools, workflows, evaluation, approvals, observability, and recovery
- * Have hands-on experience or strong practical familiarity with LLM applications, agentic systems, tool calling, retrieval, workflow orchestration, or applied AI products
- * Have strong product judgment. You can reason from customer need to product experience to technical architecture, and you know the difference between a clever demo and a dependable customer-facing system
- * Are comfortable working across ambiguity. You can take a broad problem, identify the crux, sequence the work, make tradeoffs, and keep moving without waiting for perfect clarity
- * Like building platform abstractions and shared services that help multiple teams or product surfaces move faster
- * Hold a high bar for quality, reliability, and trust. You know that systems acting on behalf of users need clear contracts, observability, evaluation, and recovery paths
- * Are energized by debugging messy production behavior across model outputs, distributed systems, product logic, user context, and downstream integrations
- * Communicate clearly with engineering, product, design, data, operations, and platform partners
- * Are motivated to actively mentor and grow others
- * Are a tenacious learner who stays engaged with the frontier of AI engineering without chasing every shiny object
- * Are motivated by measurable customer and operational impact, not just interesting technical demos
- * 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, operational quality, or other systems that make software safer and more dependable over time
- * Experience partnering deeply with Product, Design, Data, Operations, Legal, Support, or other cross-functional teams in a sensitive customer domain
- * Firsthand experience building products where customer trust, permissions, explainability, and recovery paths are central to the experience
- * A visible habit of turning repeated one-off work into reusable systems, patterns, and documentation
Benefits
- Bonus
- Health, Dental & Vision Plans
- 401k Matching
- Unlimited PTO
- Lunch daily (in-office only)
- Snacks & Coffee (in-office only)
- Commuter benefits (in-office only)
Company Overview
Company H1B Sponsorship