Senior Software Engineer, Operational AI

Brex
São Paulo, Brazil
Hybrid

Who this role is best for

Aimed at senior backend engineers with AI experience who can lead platform development and prioritize operational excellence.

Best fit for

  • Senior engineers with experience in AI-powered systems and distributed infrastructure who can lead platform evolution
    — “designing, building, and operating reliable production backend systems”
  • Candidates who have led shared infrastructure or developer tooling and care about secure-by-default design
    — “you've built shared infrastructure, developer tooling, or paved roads that other engineers adopt”
  • Individuals with a track record of shipping LLM-powered systems and evaluating their quality over time
    — “shipping LLM-powered systems to production, beyond prototypes: orchestrating model calls, enforcing structured outputs, and evaluating quality over time”

Things to consider

  • Requires a minimum of three coordinated in-office days per week despite hybrid flexibility
    — “require a minimum of three coordinated days in the office per week”
  • Prior experience with durable workflow engines like Temporal is a strong differentiator
    — “Experience with Temporal or another durable workflow engine”

How to stand out

  • Highlight experience with AI coding tools and LLM orchestration in your resume and interview narrative
    — “Deep, hands-on experience using AI coding tools like Claude Code or Cursor in your daily work”
  • Demonstrate your ability to define platform requirements and drive adoption through clear documentation
    — “Drive adoption by making the platform easy to build on through clear contracts, paved roads, documentation”
  • Showcase your work on non-deterministic systems and how you measure and improve their quality rigorously
    — “measure and improve non-deterministic systems with production-grade rigor”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • technical direction of platform
  • new platform capabilities
  • evaluation and quality system evolution
Typical background
software engineeringAI systems

Skills & requirements

Required

AIPlatform DevelopmentProduction SystemsTechnical Leadership

Preferred

PythonKubernetesDocker

Stack & domain

PythonReactTool UseMCPRetrievalAgentic LoopsML EngineeringMlopsData InfrastructureLeadershipCommunicationFinanceHealthcare

About the role

Original posting from Brex

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.

Engineering at Brex

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you'll do

Brex's AI strategy has three pillars: Product AI builds AI into the products our customers use, Corporate AI gives every employee AI tools to work faster, and Operational AI builds the AI that runs the company. The Operational AI team owns the AI systems and internal platforms that make Brex's operations AI-native, from onboarding and KYC automation to AI-powered customer support. We're a small team with a large surface area, and our work directly shapes how fast Brex can onboard, serve, and grow its customers.

As a Senior Software Engineer on the team, you'll focus on Agents Platform, Brex's internal platform for building, evaluating, and running AI agents in production. It already powers critical automations in customer onboarding and AI tools for our sales and customer success teams. You'll own its technical direction, help it evolve from simple workflows into agents that take action, and make it the default way Brex ships AI into its operations.

Where you'll work

This role will be based in our São Paulo 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

Own the technical direction and roadmap of Agents Platform, partnering with Operational AI leadership and the teams that build on it to decide what the platform should do next.

Design and build new platform capabilities, including tool calling, multi-step agent loops, multi-turn and conversational execution, and secure access to internal Brex data and services.

Evolve the evaluation and quality system, from datasets and labeling to run comparison and regression testing, so teams can measure and improve non-deterministic systems with production-grade rigor.

Strengthen the reliability, security, and observability of systems in business-critical flows like customer onboarding, including durable async and batch execution, authorization, cost attribution, and incident response.

Partner with engineering, operations, and go-to-market teams to launch and scale high-impact agents, translating how they work into clear platform requirements.

Drive adoption by making the platform easy to build on through clear contracts, paved roads, documentation, and AI-native developer workflows.

Mentor engineers on the team and across Brex through design reviews, code reviews, and pairing, and help grow the team's technical bench.

Requirements

5+ years of professional software engineering experience, with a track record of designing, building, and operating reliable production backend systems.

Deep, hands-on experience using AI coding tools like Claude Code or Cursor in your daily work, with the judgment to ship faster without lowering the quality bar.

Hands-on experience shipping LLM-powered systems to production, beyond prototypes: orchestrating model calls, enforcing structured outputs, and evaluating quality over time.

Experience with distributed and asynchronous systems and the reliability concerns that come with them, such as retries, idempotency, backpressure, and observability.

A platform mindset: you've built shared infrastructure, developer tooling, or paved roads that other engineers adopt, and you care about developer experience and secure-by-default design.

High ownership and operational excellence, including on-call, incident response, and owning systems end to end.

Strong written and verbal communication, and the judgment to prioritize across many internal customers, including non-engineers. English proficiency is required, as interviews will be conducted in English.

Bonus points

Experience building eval frameworks, LLM gateways, or agent platforms used by other teams.

Experience with Temporal or another durable workflow engine.

Experience with service and agent authorization, such as RBAC, scoped credentials, or agents acting on behalf of users.

Production experience with tool use, MCP, retrieval, or agentic loops.

A background in ML engineering, MLOps, or data infrastructure.

Experience in fintech or another regulated environment, where auditability and model governance matter.

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.

Source: Brex careers

Similar roles

More roles at Brex