Engineering Manager, AI — Brex Assistant

Proven experience leading engineering teams building user-facing products in complex, real-world domains.

Strong product judgment, with a track record of making hard tradeoffs and delivering outcomes under real constraints.

Experience building and operating systems that must remain reliable despite messy inputs, ambiguity, or non-deterministic behavior.

Ability to translate high-level product goals into clear technical direction and execution plans, while mentoring engineers through strong technical and product guidance.

Nice to have:

The expected salary range for this role is $240,000 - $300,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Please be aware, job-seekers may be at risk of targeting by malicious actors looking for personal data. Brex recruiters will only reach out via LinkedIn or email with a

brex.com

domain. Any outreach claiming to be from Brex via other sources should be ignored.

As an Engineering Manager for the Brex Assistant, you’ll lead a team building a consumer-facing conversational AI product that helps customers move faster and with more confidence in moments that matter: approving spend, understanding policy, resolving issues, and making financial decisions without friction. You’ll be accountable for both people leadership and product outcomes, guiding how agentic systems are designed, shipped, and operated in production.

This is a deeply product-driven role. Success is measured by real customer impact — better expense documentation, stronger policy compliance, and less time spent navigating Brex — not by novelty or research output.

Lead and grow a team of engineers building the end-to-end conversational experience for the Brex Assistant, including outbound system-initiated interactions and inbound chat.

Operate at all levels, guiding your team through complex technical challenges while being hands on with code and contributing to design.

Own delivery and outcomes for the Assistant roadmap, making and executing hard sequencing decisions for agent capabilities (e.g., memory, preferences, merchant data).