Staff Applied AI Engineer at Rocket Money | CA, US | Rezi

Staff Applied AI Engineer at Rocket Money

Staff Applied AI Engineer

Rocket Money · CA, US

1 months ago

Staff Applied AI Engineer

Rocket Money · CA, US

a month ago
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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 primitives that turn ambiguous product needs into shippable technical plans, prototypes, and durable systems, and partner with contact-method owners to make each method more agentic and better integrated with the Capabilities Engine.

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.

Requirements

  • Have experience shipping production software with strong engineering fundamentals.
  • Are excited by AI as an execution layer, understanding 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; can reason from customer need to product experience to technical architecture.
  • Are comfortable working across ambiguity; 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; 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.

Skills

  • LLM applications
  • Agentic systems
  • Tool calling
  • Retrieval
  • Workflow orchestration
  • Applied AI products
  • TypeScript
  • Node
  • GraphQL
  • Postgres
  • Evaluation systems for probabilistic or agentic behavior
  • Observability systems for probabilistic or agentic behavior
  • Reliability improvement
  • Alerting
  • Tracing
  • Incident response
  • Operational quality

Location

  • In-office only

Work Type

  • Full-time

Experience Level

  • Senior

Salary/Compensations

  • $200,000 - $270,000/year + bonus + benefits

Benefits

  • Health, Dental & Vision Plans
  • Competitive Pay
  • 401k Matching
  • Unlimited PTO
  • Lunch daily (in-office only)
  • Snacks & Coffee (in-office only)
  • Commuter benefits (in-office only)

About the Company

  • 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.
  • 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?”

Equal Opportunity

  • Decisions related to employment are not based on race, color, religion, national origin, sex, physical or mental disability, sexual orientation, gender identity or expression, age, military or veteran status or any other characteristic protected by state or federal law.
  • The company provides reasonable accommodations to qualified individuals with disabilities in accordance with applicable state and federal laws.
  • Los Angeles County and San Francisco Candidates only: qualified applicants with arrest or conviction records will be considered for employment per the Fair Chance Ordinance and the Fair Chance Initiative for Hiring.