[Hiring] Staff Applied AI Engineer @Rocket Money

Role Description

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.

• Create the primitives that capability teams need to turn ambiguous product needs into shippable technical plans, prototypes, and durable systems.
• Partner with contact-method owners across phone, email, chat, web login, ODC, and autonomous workflows to enhance integration with the Capabilities Engine.
• Help agents plan, discover and invoke capabilities, recover from ambiguity, handle real-world edge cases, and complete user-facing work safely and correctly.
• Build systems that let agents use tools, observe outcomes, recover from failure, and earn enough trust to act on behalf of users.
• Work across product and platform boundaries, moving between architecture, implementation, debugging, evaluation, and cross-functional collaboration.
• Ensure new capabilities ship with clear contracts, tests, traces, ownership, and production-readiness expectations.

Qualifications

• Experience shipping production software with strong engineering fundamentals.
• Excited by AI as an execution layer, understanding that durable customer value comes from orchestration, tools, workflows, evaluation, approvals, observability, and recovery.
• Hands-on experience or strong practical familiarity with LLM applications, agentic systems, tool calling, retrieval, workflow orchestration, or applied AI products.
• Strong product judgment, able to reason from customer need to product experience to technical architecture.
• Comfortable working across ambiguity, identifying the crux of broad problems and making tradeoffs.
• Interest in building platform abstractions and shared services that help multiple teams or product surfaces move faster.
• High bar for quality, reliability, and trust, knowing that systems acting on behalf of users need clear contracts, observability, evaluation, and recovery paths.
• Energized by debugging messy production behavior across model outputs, distributed systems, product logic, user context, and downstream integrations.
• Clear communication with engineering, product, design, data, operations, and platform partners.
• Motivated to actively mentor and grow others.
• Tenacious learner, engaged with the frontier of AI engineering.
• Motivated by measurable customer and operational impact, not just interesting technical demos.

Requirements

• 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

• 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)
• Salary range of $200,000 - $270,000/year + bonus + benefits.