Senior Full Stack Engineer, AI Products - Stout Strategy

Stout•Arlington, VA

About The Position

The Senior Full Stack Engineer will join Stout Strategy’s Applied Innovation Group, working on Flightline, an AI-native platform designed to improve how consulting research, analysis, and insights are produced. The role offers the opportunity to work across the stack on a product used by consultants in live client work, owning meaningful areas of the platform as adoption grows across the firm. The engineer will collaborate closely with the Managing Director, Applied Innovation, other engineers, and UI/UX and product colleagues. The role involves building and shipping frontend and backend features, contributing to LLM-backed product capabilities, and creating tests and evaluation systems that make AI-generated work reliable. The engineer will use AI coding agents as part of the development workflow, while applying judgment to review their output and write code directly when appropriate. They will also work with consultants, product, and design to refine requirements and will be expected to learn unfamiliar parts of the platform, tools, and consulting domain as needed.

Requirements

At least five years of professional full-stack software engineering experience, including user interfaces, server-side logic, APIs, data stores, background processing, and operating software in production.
Experience shipping and operating software; demonstrated production work is valued more than years alone.
Ability to become productive in unfamiliar stacks, codebases, domains, or tools and contribute meaningfully.
Ability to understand how logic and data flow through a system and trace problems across its components.
Experience owning a system area through production and beyond, with comfort taking on varied responsibilities and prioritizing effectively.
Daily use of AI coding tools, including writing clear specifications and acceptance criteria, reviewing output closely, knowing when to code manually, and building safety checks for AI-assisted changes.
Clear written and spoken communication, including explaining technical trade-offs to consultants without jargon.
Experience with LLM applications such as retrieval, structured output, orchestration, and context management.
Ability to turn qualitative feedback about output quality into testable checks, such as evaluations.
Interest in how consultants and deal teams work.

Nice To Haves

Experience with React, TypeScript, or Python; these are used by the team but are not required.

Responsibilities

Ship features from refined requirements through production across frontend and backend.
Own areas of the platform, such as a data pipeline, service, or part of the user interface.
Work on LLM-backed product capabilities, including extraction, retrieval, chat, and content generation, and help measure and improve output quality.
Use AI coding agents in the development workflow by breaking work into well-specified tasks, reviewing agent output, and writing code manually when faster or safer.
Build tests, evaluations, and checks to verify AI-assisted changes and make them safe to ship.
Address the team’s changing needs, including bugs in unfamiliar code, integrations, and tools for consultants.
Partner with consultants, product, and design to clarify and sharpen requirements.
Take ownership of problems and system areas through production and follow-up.
Build small versions to validate ideas and reduce scope when appropriate.
Document design notes, decisions, and hand-offs.
Learn how consultants use the platform and understand the purpose of features before building them.