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

About us AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re number one or two in many of the world’s top beer markets, including North America, Latin America, Europe, Asia, and Africa. About AB InBev Growth Group Created in 2022, the Growth Group unifies our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and Marketing teams. By bringing together global tech and commercial functions, the Growth Group allows us to fully leverage data and drive digital transformation and organic growth for AB InBev around the world. In addition to supporting well known global beer brands like Corona, Budweiser and Michelob Ultra, the Growth Group is home to a robust suite of digital products including our B2B digital commerce platform BEES, on-demand delivery services Ze Delivery and TaDa Delivery, and table top beer keg PerfectDraft. We are an exceptional team, focused on understanding and supporting consumer and customer needs, harnessing new technology, and scaling growth opportunities. 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. Diagnose and fix reliability issues, and lead incident response and blameless postmortems. Establish safe rollout practices: feature flags, canary releases, and fast rollback. Design and raise the bar Write design docs for the components you deliver, compare alternatives with data and prototypes, and escalate risk to the Staff Architect. Raise the team's technical bar through code review, pairing, and standards for testing, observability, and safe rollout. Use coding agent harnesses such as Cursor, Claude Code, and Codex as part of yo