Rocket Money is a subscription manager that helps find and cancel unwanted subscriptions, and helps you create a custom budget to track monthly spending and expenses. Backed by Accel.
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. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 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
More about this role
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?”
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,...
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