What you'll doWe're building AI agents to automate and augment internal functions at Brex, and we're looking for a hands-on builder to help us do it. You'll embed with teams across the company to understand how they actually work, then design, build, and ship agents that deliver real outcomes. You'll work on top of existing models and frameworks, wiring together tools, MCPs, and internal systems into agentic workflows. This is a technical role where you'll spend most of your time building, shipping, and iterating alongside the people whose work you're automating.
Where you'll workThis 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 currently require a minimum of 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:- Embed with partner teams to deeply understand workflows, including shadowing and learning different job functions.
- Scope, design, and deploy agents that take over real workflows across internal orgs.
- Integrate agents with internal systems, APIs, and data sources.
- Define evaluation frameworks, success metrics, and feedback loops to measure and improve agent performance.
- Build shared tooling and contribute to playbooks that accelerate deployments, while owning reliability, adoption, and business impact.
Requirements:- 4+ years in engineering, technical product/program management, applied AI, or a similar technical role, with a track record of shipping AI/automation systems to production.
- Hands-on experience building with LLMs, agent frameworks, and tool-use patterns (e.g., MCP, function calling, RAG) across the full stack (data, APIs, orchestration, product).
- Experience designing and optimizing SQL and/or NoSQL databases, including data modeling, query performance tuning, and schema design.
- Strong ability to decompose human workflows into scalable, agentic systems, grounded in a deep curiosity for how people work.
- High ownership and cross-functional influence, with the ability to quickly build trust across teams and seniority levels.
Bonus points- Experience automating back-office functions rather than just customer-facing AI features.
- Experience with OpenClaw, Hermes, or other general-purpose agent harnesses.
Compensation:The expected salary range for this role is $152,000 - $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.
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.
