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

Accountabilities:: Design, implement, test, deploy, and operate backend services against explicit latency, availability, reliability, and cost targets, taking ownership of features throughout their production lifecycle. Build and maintain typed, versioned API contracts while evolving services safely without breaking existing clients, and manage authentication, authorization, and multi-tenant access controls across the application. Deliver features end to end, including backend APIs and user interfaces when required, while integrating the application with internal services and AI or agent services through reliable patterns for streaming, timeouts, cancellation, and partial failures. Own the read path over analytical data, including data modeling, query planning, pagination, batching, caching, and consistency decisions, while continuously improving application performance and efficiency. Establish and defend performance budgets by profiling services, reducing tail latency such as p95 and p99 response times, optimizing cost per request, and conducting load and capacity testing before major releases. Build strong observability into owned services through metrics, structured logging, distributed tracing, SLIs, SLOs, alerts, and dashboards, while participating in on-call activities and leading incident response and blameless postmortems. Implement safe deployment and operational practices, including feature flags, canary releases, fast rollback mechanisms, automated testing, and reliable release processes. Produce design documentation, evaluate architectural alternatives using measurements and prototypes, escalate risks appropriately, and raise the team's engineering standards through code reviews, pairing, testing, observability, and safe rollout practices. Incorporate coding agent tools such as Cursor, Claude Code, and Codex into the development workflow while critically reviewing generated code against tests, types, contracts, and production-quality standards. Requirements Hold a bachelor's degree in computer science, engineering, mathematics, or another quantitative discipline; a master's degree or PhD is a plus. Bring relevant experience designing, building, deploying, and operating distributed backend services in production, with strong understanding of coding standards, code review, automated testing, deployment, and operations. Demonstrate a proven track record of taking features from initial design through production and maintaining ownership of them in live environments, including experience designing software for reliability and scale. Have deep expertise in at least one high-performance programming language such as Java/Kotlin, Go, Rust, C++, or C#, including a strong understanding of its memory model, concurrency model, and runtime. Be productive in Python, which is used across the current services, and possess relevant full-stack production experience with TypeScript and a modern web framework. Demonstrate hands-on production experience with observability, including metrics, distributed tracing, structured logging, SLOs, and tools such as OpenTelemetry, Datadog, Grafana, or Prometheus. Possess proven performance-engineering experience involving profiling, query optimization, caching strategies, load testing, capacity planning, and reduction of tail latency. Have strong distributed-systems knowledge, including timeouts, retries, idempotency, partial failures, streaming technologies such as SSE or WebSockets, and performance decisions based on p95 and p99 latency. Demonstrate day-to-day fluency with coding agent harnesses such as Cursor, Claude Code, and Codex, including the ability to critically evaluate and validate AI-generated code. Communicate clearly in writing and verbally, with the ability to explain architecture, technical decisions, and trade-offs in depth to experienced engineering stakeholders. Possess advanced English communication skills; Spanish is considered a plus. Experience with analytical data serving layers such as OLAP, columnar databases, semantic layers, or data platform integrations is advantageous. Experience consuming LLM or agent services, working with B2B, multi-country, or multi-tenant products, and using cloud platforms such as Azure, AWS, or GCP, containers, and Kubernetes is a plus. Benefits Performance-based bonus, subject to applicable rules. Attendance bonus, subject to applicable rules. Private pension plan. Meal allowance and transport allowance. Health, dental, and life insurance. Medicines discounts. WellHub partnership. Childcare subsidies and school materials assistance. Discounts on company products, subject to applicable rules. Clube Ben partnership. Scholarship opportunities, subject to applicable rules. Access to language and professional training platforms. Days off, subject to applicable rules. Opportunity to work in a senior, hands-on engineering environment focused on modern distributed systems, AI-enabled development, data-intensive applications, and continuous technical growth.