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.

What you’ll do

You’ll own Brex’s simulation and validation platform for AI-powered products. Your mandate is simple and unforgiving: ensure that every AI surface at Brex is continuously scrutinized under extreme, realistic conditions — and that teams can ship with confidence because of it.

You’ll build a system that uses synthetic data and scenario generation as a recursive self-improvement loop. Product teams will rely on it to catch regressions before customers do, to validate new capabilities safely, and to evolve prompts and agent behavior continuously. This platform will run against isolated, ephemeral environments that mirror production closely enough to matter.

This is not a research role. It’s about exercising real products, breaking them creatively, and forcing the organization to get better.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We require three coordinated days in the office per week — Monday, Wednesday, and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Evolve and scale a simulation and validation platform to continuously stress-test Brex’s AI products using large-scale synthetic data.
• Develop evaluation mechanisms to detect regressions, edge cases, and failure modes in non-deterministic systems prior to customer impact.
• Run continuous testing in isolated, production-like environments and set quality gates, including authority to block launches when standards are not met.
• Partner closely with product engineering teams to improve system testability, isolation, and overall robustness.
• Define and uphold company-wide standards for AI feature quality, using simulation-driven insights to guide prompt and system evolution, while driving the technical bar for a small, high-impact team.

Requirements

• Experience building and owning complex software systems where correctness, reliability, and failure modes are critical.
• Experience designing test, simulation, or validation systems for non-deterministic or high-stakes environments.
• Strong systems thinking, with the ability to decompose complex problems and reduce incidental complexity.
• Demonstrated ability to influence product architecture through quality, reliability, and launch-readiness constraints.
• Comfort operating with real authority and cross-team influence, including blocking launches and partnering across seniority levels to raise the quality bar.

Bonus points

• Previous experience on simulation or testing of inherently complex systems (AI/ML, distributed systems, robotics, IoT, medical devices, aerospace, defense, etc.).
• Experience building internal platforms that became critical shared infrastructure.
• Strong intuition for failure modes in real-world systems.

Compensation

The expected salary range for this role is $192,000 - $240,000. 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.