Engineering Manager, AI — Brex Assistant

Brex Brex · Fintech · San Francisco, CA +1 · Engineering

Engineering Manager for Brex Assistant, a consumer-facing conversational AI product. Leads a team building end-to-end agentic systems for financial workflows, focusing on product outcomes and customer impact. Requires strong leadership, product judgment, and experience with complex, real-world AI systems.

What you'd actually do

  1. 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.
  2. Operate at all levels, guiding your team through complex technical challenges while being hands on with code and contributing to design.
  3. Own delivery and outcomes for the Assistant roadmap, making and executing hard sequencing decisions for agent capabilities (e.g., memory, preferences, merchant data).
  4. Set and uphold a high bar for reliability, correctness, and UX in non-deterministic, agentic systems operating in real-world financial workflows.
  5. Partner closely with Product, Design, and adjacent engineering teams (Spend, Expense, Platform) to shape direction and integrate deeply with core Brex workflows.

Skills

Required

  • 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

  • Development experience with Typescript while leading consumer-facing AI products, especially in regulated or high-stakes domains (finance, healthcare, travel).
  • Direct experience with conversational UX, agents, or other non-deterministic systems in production.
  • Prior experience as a tech lead for agentic systems, particularly in spend or financial workflows.
  • Personal empathy for spend-heavy workflows (frequent travel, recruiting, managing expenses on behalf of a company).

What the JD emphasized

  • consumer-facing conversational AI product
  • agentic systems
  • non-deterministic, agentic systems operating in real-world financial workflows
  • complex, real-world domains
  • messy inputs, ambiguity, or non-deterministic behavior
  • regulated or high-stakes domains (finance, healthcare, travel)

Other signals

  • AI agents that take action
  • consumer-facing conversational AI product
  • agentic systems