AI Engineer, Product
Why Join Us
Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek.
AI at Brex
AI Engineering at Brex is redefining how businesses run their finances by building intelligent, autonomous systems directly into the Brex platform. Our teams develop AI agents that don’t just surface insights—they take action, optimizing spend, managing workflows, and making real-time decisions on behalf of our customers. By deeply integrating proprietary financial data with product and platform infrastructure, we’re turning complex financial operations into simple, automated experiences and setting a new standard for how modern finance works.
Responsibilities
- Build and ship customer-facing features in production — from sketch to rollout to iteration based on real customer feedback.
- Define the data contracts between the agent and the rest of Brex's financial system of record, and evolve them as the product gets sharper.
- Stand up feedback and evaluation loops that let us quickly gather product signals and close them with product fixes — better signals, better surfaces, better workflows.
- Talk to customers and reviewers directly, bring what you learn back into the product, and prioritize what to build next on the team.
Requirements
- Strong track record of shipping customer-facing features end-to-end across both backend and frontend — you don't bounce work over a wall, and you've built enough of each to have real opinions.
- Product mindset: you reason about users, workflows, and outcomes first, and treat the system as the means to an end. Comfort with ambiguity and willingness to talk to customers directly.
- Strong bias towards action — you've operated in environments where the next thing to build wasn't handed to you in a ticket, and you've shipped things that didn't exist before.
- Comfort working across team boundaries and pushing back on decisions outside your direct ownership when the seam isn't right — agent design, UX, data model, all fair game.
- Strong backend foundation — system design, data modeling, API shape — and the disposition to ship the UI yourself when that's what the user problem needs, rather than handing it off
Bonus Points
- Early-stage startup experience, or time on a small team where you owned a product surface end-to-end.
- Experience building products on top of LLMs or agentic systems — particularly the surrounding harness (evaluation, tracing, feedback loops, human-in-the-loop workflows).
- Background in fintech, compliance, audit, fraud, or other domains where review workflows and traceability matter.
- Experience operating where the underlying system is non-deterministic and the product has to compensate for that.
- Track record of being the engineer teams pull in when a project is stuck across backend, frontend, and a third system that nobody fully owns.
Compensation
The expected salary range for this role is $171,000 - $240,000 USD. 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.
Brex LLC is a wholly owned subsidiary of Capital One, N.A.
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.