Staff Full-Stack Engineer - Data Intensive Web-Applications - Personalization

About the role

About BEES

Join us to build the future of B2B commerce! BEES is AB InBev’s B2B platform. Through our ecosystem, merchants and retailers across 29 countries can stock their businesses quickly, easily, and securely. At BEES, we dream big, lead with purpose, and develop technology that transforms the way retailers and sellers grow. Every line of code and every partnership is built in service of a single mission: to make commerce better for retailers and sellers around the world. Here, your work is not just important. It makes a difference!

About the Role:

As a Staff Full Stack Engineer (Backend Focus), you will build and operate the backend of a Web Analytics and AI portal. That includes the APIs that serve the application, the read data layer over analytical data, authentication and authorization, and the integration points with the services the rest of the team builds. The portal gives commercial intelligence to the people who make business decisions, through daily briefings, customizable KPIs, analytical insights, geographic exploration, and conversational analytics.

This is a Staff (L6), hands-on individual contributor role on a lean team where everyone is Staff: a Staff Architect, Staff AI Engineers, Staff Software Engineers, and Data Engineers. Architectural direction sits with the Staff Architect, and the AI Engineers own the agents. You are the builder: you take features from the design doc to production, end to end, and you make them fast, observable, and reliable. Most of your time goes to writing, reviewing, and operating code, including the user interface when the delivery calls for it.

What you'll do:

Build the backend and ship features end to end

- Design, implement, test, and operate backend services against explicit latency, availability, and cost targets.

- Implement typed, versioned API contracts and evolve them without breaking clients.

- Own authentication, authorization, and multi-tenant access control across the portal.

- Ship features end to end, from the API to the interface, when the delivery calls for it.

- Integrate the application with internal services, including the agent services built by the AI Engineers. This covers response streaming, timeouts, cancellation, and partial failures.

Own the read path and performance

- Own the read path over analytical data: data modeling, query plans, pagination, batching, caching, and consistency trade-offs.

- Set and defend performance budgets. Profile services, reduce tail latency (p95, p99), and optimize cost per request.

- Run load and capacity tests before launches, and use the results to make design decisions.

Make systems observable and reliable

- Instrument services with metrics, structured logs, and distributed tracing from day one.

- Define SLIs and SLOs, alerts, and dashboards for the components you own, and take part in on-call.