AI Engineer, Product
Brex · San Francisco, California, United States
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.
Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career.
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 be a product engineer building Brex's Audit Agent — an agentic system that reviews customer spend at scale and replaces the manual work traditionally done by BPO teams. The agent itself reasons; the surrounding product harness is what makes that reasoning useful, trustworthy, and operable for real customers.
That product harness is where you'll live. You'll design and ship the workflows, surfaces, and data flows that turn the agent's output into something a reviewer can trust and act on — from the reviewer experience itself, to the contracts with Brex's financial system of record, to the feedback loops that make the agent better over time. You'll move fluidly between backend and frontend as the work demands, picking the right altitude for the problem rather than defending a layer.
This role sits between deep agent design and the customer-facing UI, and it leans toward whichever side the next user problem lives on. You'll partner closely with the engineers driving each — translating ambiguous product requirements into shipped features, pushing back when the design isn't right, and treating the seam between agent reasoning and human workflow as a first-class product surface.
The majority of your work will be backend: system design, data modeling, API shape. A meaningful minority will be on the UI itself, where you'll build alongside our frontend engineers when that's where the next user problem lives.
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
• 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.
• Run experiments on customer-facing behavior (UI flows, prompt-driven product changes, new review modes) and make calls based on what the data says.
• 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
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.
Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career.
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 be a product engineer building Brex's Audit Agent — an agentic system that reviews customer spend at scale and replaces the manual work traditionally done by BPO teams. The agent itself reasons; the surrounding product harness is what makes that reasoning useful, trustworthy, and operable for real customers.
That product harness is where you'll live. You'll design and ship the workflows, surfaces, and data flows that turn the agent's output into something a reviewer can trust and act on — from the reviewer experience itself, to the contracts with Brex's financial system of record, to the feedback loops that make the agent better over time. You'll move fluidly between backend and frontend as the work demands, picking the right altitude for the problem rather than defending a layer.
This role sits between deep agent design and the customer-facing UI, and it leans toward whichever side the next user problem lives on. You'll partner closely with the engineers driving each — translating ambiguous product requirements into shipped features, pushing back when the design isn't right, and treating the seam between agent reasoning and human workflow as a first-class product surface.
The majority of your work will be backend: system design, data modeling, API shape. A meaningful minority will be on the UI itself, where you'll build alongside our frontend engineers when that's where the next user problem lives.
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
• 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.
• Run experiments on customer-facing behavior (UI flows, prompt-driven product changes, new review modes) and make calls based on what the data says.
• 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
71,000 -
40,000 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.
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Public study materials
- Python (Python)
- Python Fundamentals · basic
- Control Flow · basic
- Strings · basic
- Collections / Data Structures · basic
- Functions · basic
- Modules and Packages · basic
- File Handling · basic
- Exception Handling · basic
- Object-Oriented Programming (OOP · medium
- Advanced Python Concepts · advance
- Functional Programming · advance
- Multithreading & Multiprocessing · advance
- Async Programming · advance
- System Architecture (System Architecture)
- Fundamentals of System Architecture · basic
- Distributed System Basics · basic
- System Reliability Concepts · basic
- Scaling Concepts · basic
- Networking Basics · basic
- Web Communication · basic
- API Communication · basic
- Proxy & Delivery Systems · basic
- Web Architecture Basics · basic
- Rendering Architectures · basic
- Frontend Advanced Concepts · basic
- Message Queue Basics · medium
- What is Load Balancer · medium
- Load Balancing Algorithms · medium
- API Design Basics · medium
- API Protection · medium
- Authentication Basics · medium
- Security Tokens · medium
- Security Threats · medium
- Encryption & Security · medium
- SQL Database Basics · medium
- SQL Scaling Concepts · medium
- NoSQL Databases · medium
- Database Optimization · medium
- Replication Strategies · medium
- Caching Basics · medium
- Cache Storage Systems · medium
- Cache Strategies · medium
- Event-Driven Systems · advance
- Queue Reliability · advance
- Microservices Basics · advance
- Microservice Communication · advance
- Distributed Transactions · advance
- DevOps Basics · advance
- Automation Tools · advance
- Deployment Strategies · advance
- Monitoring Basics · advance
- Monitoring Tools · advance
- Distributed System Concepts · advance
- Distributed Algorithms · advance
- Express.js — Web APIs & middleware (expressjs)
- Application setup · basic
- Routing deep dive · basic
- 1. MVC / Layered Architecture · medium
- Validation · medium
- File uploads · medium
- Sessions & auth (stateful) · medium
- Passport & strategies · medium
- Templating & SSR · medium
- WebSockets & SSE · medium
- Security middleware · advance
- Reverse proxies & trust · advance
- Performance · advance
- API design & versioning · advance
- Testing with Supertest · advance
- GraphQL & tRPC (overview) · advance
- Deployment checklist · advance
- Middlewares · basic
- Request & Response · basic
- System Designing (System Designing)
- Day-1 : What is system Designing ? · basic
- Day-2 : Vertical vs. Horizontal Scaling · basic
- Day-3:How to do vertical scaling ? · basic
- Day4:How to do horizaontal scaling ? · basic
- Day:5TCP vs UDP · basic
- Day6:IP & DNS · basic
- Day7:Client-Server Model · basic
- Day8:HTTP & HTTPS · basic
- Databases (SQL vs NoSQL) · medium
- Caching · medium
- Day9:Latency & Throughput · basic
- Load Balancing · medium
- Indexes & Query Optimization · medium
- CDN · medium
- Proxies · medium
- Message Queues · medium
- Horizontal vs Vertical Scaling · medium
- Database Replication · advance
- Database Sharding · advance
- Consistent Hashing · advance
- CAP Theorem · advance
- Rate Limiting · advance
- Service Discovery · advance
- Event-Driven Architecture · advance
- API Gateway · advance
- Distributed Consensus · expert
- Microservices · expert
- Observability · expert
- Idempotency · expert
- PACELC Theorem · expert
- Two-Phase Commit · expert
- Back-of-Envelope Estimation · expert
- Designing for Failure · expert
- SQL (SQL)
- SQL Fundamentals · basic
- Database Operations · basic
- Table Operations · basic
- CRUD Operations · basic
- Filtering & Operators · basic
- SQL Functions · basic
- GROUPING Data · basic
- Joins · medium
- Constraints · basic
- Subqueries · medium
- Set Operators · medium
- Views · medium
- Indexes · medium
- Normalization · advance
- Transactions · advance
- Stored Procedures & Functions · advance
- Triggers · advance
- Advanced SQL · advance
- Query Optimization · advance
- Database Design · advance
- SQL Security · advance
- Backup & Recovery · advance
- Questions · interview questions
- Django (Django)
- What is Django · basic
- Installing Django · basic
- Features of Django · basic
- MVT Architecture · basic
- Django vs Flask · basic
- Creating Project & Creating App · basic
- Django Project Structure · basic
- URL Routing · basic
- Views · basic
- Templates · basic
- Static & Media Files · medium
- Models · medium
- ORM (Object Relational Mapping) · medium
- Model Relationships · medium
- Migrations · medium
- Django Admin · medium
- Forms · medium
- Authentication · medium
- Authorization · medium
- Middleware · medium
- Signals · medium
- Class Based Views Deep Dive · advance
- Generic Views · advance
- File Handling · advance
- Django REST Framework (DRF) · advance
- Advanced ORM · advance
- Caching · advance
- Asynchronous Django · advance
- Background Tasks · advance
- Interview Questions · interview-questions
- JavaScript (JavaScript)
- JS Introduction · basic
- Variables & Data Types · basic
- Operators · basic
- Control Flow · basic
- Functions · basic
- Scope & Execution · basic
- Closures · basic
- Objects · basic
- Arrays · basic
- Strings · basic
- DOM Manipulation · basic
- Browser APIs · medium
- Asynchronous JavaScript · medium
- Fetch & APIs · medium
- ES6+ Features · medium
- OOP in JavaScript · medium
- Prototype & Inheritance · advance
- Advanced Functions · advance
- Memory Management · advance
- Error Handling · advance
- Modules · advance
- Advanced Async Concepts · advance
- Functional Programming · advance
- JavaScript Internals · advance
- Performance Optimization · advance
- Angular (Angular)
- Angular Fundamentals · basic
- Project Structure · basic
- Components & Templates · basic
- Data Binding · basic
- Directives · basic
- Pipes · basic
- Component Communication · basic
- Lifecycle Hooks · basic
- Routing Basics · basic
- Routing · basic
- API Calls · basic
- Forms · medium
- Routing · medium
- Services & Dependency Injection · medium
- RxJS & Observables · medium
- Authentication & Security · medium
- Component Interaction · medium
- State Management Basics · medium
- Error Handiling · medium
- Perfomance Basic · medium
- Real World Features · medium
- Advanced Angular Architecture · advance
- Change Detection · advance
- Advanced RxJS · advance
- State Management · advance
- Dynamic Rendering · advance
- Perfomance Optimization · advance
- Modern Angular · advance
- STAR (Situation, Task, Action, and Result) (Situation Based Questions)
- Node.js — Server-side JavaScript (nodejs)
- Getting started · basic
- JavaScript on the server · basic
- CommonJS modules · basic
- ES modules (ESM) · basic
- npm & package management · basic
- Asynchronous JavaScript in Node · basic
- The event loop · basic
- Essential core utilities · basic
- process & configuration · basic
- File system basics · basic
- HTTP & HTTPS servers · medium
- Streams · medium
- Events & EventEmitter · medium
- Advanced filesystem · medium
- crypto · medium
- Compression & encoding · medium
- Child processes · medium
- net, dgram & DNS · medium
- readline, timers & scheduling · medium
- Testing & diagnostics (intro) · medium
- Worker threads · advance
- cluster & multi-process scaling · advance
- Performance & tuning · advance
- Debugging & observability · advance
- Security hardening · advance
- Native addons & N-API · advance
- Architecture patterns · advance
- Graceful shutdown · advance
- 100 Questions · interview questions
- MongoDB — Documents & data modeling (MongoDB)
- Introduction · basic
- Shell, Compass & tools · basic
- Databases & collections · basic
- CRUD operations · basic
- Indexes deep dive · medium
- Explain plans & performance · medium
- Aggregation framework · medium
- Schema design patterns · medium
- Mongoose basics · medium
- Mongoose advanced · medium
- Drivers & connection · medium
- Operators for updates & arrays · medium
- Replication & read preferences · advance
- Write concern & read concern · advance
- Multi-document transactions · advance
- Change streams · advance
- Sharding (overview) · advance
- Atlas Search & full-text · advance
- GridFS & large files · advance
- Backup, restore & ops · advance
- AWS Crash Course (AWS)
- What is Cloud ? · basic
- What is AWS ? · basic
- If not cloud ? · basic
- Cloud Computing · basic
- AWS Pricing · basic
- AWS Shared Responsibility Model · basic
- AWS Management Console · basic
- AWS SDKs · basic
- AWS IAM · medium
- Users, Groups, Roles · medium
- Policies · medium
- AWS Organizations · medium
- AWS Cognito · medium
- AWS Directory Service · medium
- AWS KMS (Key Management Service) · medium
- AWS Secrets Manager · medium
- AWS Shield · medium
- AWS WAF · medium
- AWS Inspector · medium
- AWS GuardDuty · medium
- EC2 · advance
- Launching EC2 Instances · advance
- EBS Volumes · advance
- Security Groups · advance
- Key Pairs · advance
- Elastic IP · advance
- User Data Scripts · advance
- Auto Scaling · advance
- Load Balancers · advance
- ALB · advance
- NLB · advance
- Serverless Compute ,AWS Lambda, Lambda Layers · advance
- Event-Driven Architecture · advance
- ECS · advance
- EKS · advance
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.