Staff Software Engineer, Retirement AI

Role overview

A senior engineering role on a small, focused AI product team building practical, customer-facing experiences for a retirement savings product. The position centers on hands-on implementation of large language model features, end-to-end ownership of problems, and rapid iteration from idea to production. It suits an engineer who enjoys making pragmatic technical calls and collaborating closely with product and design partners.

Responsibilities

• Design, build, and ship production features that use large language models to address real customer needs.
• Implement and integrate LLM components such as prompting strategies, tool-use loops, retrieval-augmented generation flows, evaluation harnesses, and monitoring.
• Make pragmatic architecture decisions, de-risk tricky areas, and keep workstreams unblocked.
• Partner with product and design to refine concepts, shape scope, and iterate quickly on end-to-end experiences.
• Collaborate with adjacent engineering teams to integrate with existing systems and resolve dependencies.
• Write clear, reliable, well-tested code that ships quickly and scales appropriately.

Requirements

• 7+ years of software engineering experience building and shipping production products or platforms.
• Hands-on experience implementing LLM-powered features, for example RAG flows, agents, tool loops, or workflow automation with language models.
• Strong engineering fundamentals across services, APIs, and data flows, with comfort spending most of the time coding.
• Experience running or heavily contributing to a team's execution, including sprints, ticket tracking, scoping, and cross-functional coordination.
• A bias to action: defaulting to trying things, iterating, and learning rather than waiting for direction.
• Proficiency with Ruby on Rails (or a comparable language) and React (or a comparable frontend library).
• Clear communication skills and the ability to work effectively with product, design, and other engineering teams without needing a formal management title.

Nice to have

• Familiarity with evaluation, monitoring, and observability practices for AI-powered features.
• Experience operating within hybrid, multi-office product organizations.

Benefits and work setup

• Targeted cash compensation of $187,000-$234,000 in Denver and most remote locations, and $227,000-$284,000 for San Francisco and New York, with final offers varying by experience and expertise.
• Stock equity in addition to base pay.
• Hybrid expectation of roughly 2-3 days per week in office for employees based in Denver, San Francisco, or New York; remote work permitted from other locations subject to a secure, reliable internet connection.
• Full-time employees receive competitive base pay, benefits, and equity (RSUs).