Full Stack AI Product Engineer

WHO YOU’LL WORK WITH

As the premier consulting partner for the private equity industry, Bain's PEG boasts a global practice that is over three times larger than any competitor. Our network of over 1,000 professionals supports private equity and institutional investor clients through every stage of the investment life cycle, from deal generation and due diligence to portfolio value creation and exit planning.

Bain & Company is developing a suite of cutting‑edge data and software solutions designed to revolutionize how the private equity industry uses data for investment insights and decision‑making.

The PEG Innovation team's mission is to create analytical solutions for Bain clients, teams, and the broader institutional investor space using proprietary software and data products. This includes the development, commercialization, and daily management of Bain's proprietary datasets, data, and software businesses.

Full-Stack AI Product Engineers build and deliver end-to-end AI product experiences across the PE due diligence platform. This role sits at the intersection of product engineering and applied AI, combining solid full-stack software engineering with practical knowledge of how LLMs and agentic systems behave in production.

You will build intelligent product features from backend services through frontend experience, contributing to the workflows, orchestration layers, and user interfaces that make AI useful, reliable, and intuitive for end users. This includes implementing agent workflows, retrieval pipelines, evaluation gates, human‑in‑the‑loop review patterns, and the analyst‑facing experiences that surface them. You are technically strong in production AI systems and capable of translating non‑deterministic model behavior into clear, trustworthy product experiences with guidance from senior engineers.

You will contribute to engineering standards, participate in code reviews, and grow your expertise in building safe, observable, and scalable AI‑powered workflows.

You will own intelligent product features from backend orchestration through frontend experience, building the services, workflows, and user interfaces that make AI useful, reliable, and intuitive for end users. This includes designing agent workflows, retrieval pipelines, evaluation gates, human‑in‑the‑loop review patterns, and the analyst‑facing experiences that surface them. You are deeply technical about production‑grade AI systems, but equally strong in translating non‑deterministic model behavior into clear, trustworthy, and effective product experiences.

You will mentor other engineers, raise standards for AI product engineering, and help define how Bain builds safe, observable, and scalable AI‑powered workflows.

• Build end‑to‑end AI product features across backend services, orchestration layers, and frontend user experiences.
• Develop analyst‑facing and internal AI interfaces for workflows such as deal screening, commercial due diligence research, document extraction, and portfolio monitoring.
• Build responsive, high‑quality frontend experiences for streaming AI responses, structured outputs, source grounding, review and approval flows, and human‑in‑the‑loop interactions.
• Implement full‑stack application patterns for chat, copilot, workspace, and review‑based AI experiences, including state management, real‑time updates, and error handling.
• Collaborate with Product, Design, and domain stakeholders to translate AI capabilities into intuitive, polished user experiences.
• Contribute to stable contracts between frontend applications and AI/backend services, ensuring outputs are structured, testable, and resilient.
• Support contribution workflows and product surfaces for the Prompt Execution Sandbox and AI Artifact Studio, enabling safe and scalable use by non‑engineers where required.
• Ensure AI product features are accessible, observable, and production‑ready, with attention to usability, reliability, and edge‑case handling.

• Contribute to the Agent Gateway service, including inbound APIs, model routing, context…