Senior/Lead Full-Stack Engineer

We are looking for a Senior/Lead Full-Stack Engineer with a strong backend and product-integration focus, who will also play a key role in shaping engineering standards and development practices across the team. This person will take ownership of turning business workflows and early MVPs into reliable, production-ready applications — and will establish the patterns and guidelines others follow, using our agreed engineering stack. You move comfortably across product UI, backend APIs, database design, integrations, and production readiness — and you take real satisfaction in building not just features, but the foundation others build on. Work split: ~70% backend/architecture/integrations, ~30% frontend/product workflows. This is not a people management role — impact comes through technical leadership: decisions, standards, and code. Lead architecture decisions for our Internal Operational Platform and connected tooling, and define the engineering standards and code quality practices the team follows Build and maintain full-stack applications (Java/Spring Boot + React/TypeScript), turning vibe-coded MVPs and prototypes into clean, production-ready services with typed APIs, proper auth, persistence, and observability Design PostgreSQL schemas and Liquibase migrations, and integrate BigQuery reads and publish layers Champion OpenAPI-first development and typed frontend API clients Own backend observability (Actuator, Prometheus, structured logs) Partner with business stakeholders to preserve product intent while raising technical quality What We're Looking For Backend: Java 21, Spring Boot 3.x, REST/OpenAPI contract-first development, PostgreSQL + Liquibase, Spring Security, and observability tooling (Actuator, Prometheus). Bonus if you've defined backend architecture standards, worked in multi-module Maven projects, or integrated legacy systems without rewriting them. Frontend: React + TypeScript, API-driven UI, server-state management (e.g. TanStack Query), and a good instinct for loading/error/empty states and practical workflow UIs. Data & Integration: Experience with BigQuery or a similar warehouse, and comfort reasoning about versioned data, source-of-truth boundaries, freshness, and cache/fallback behavior. Nice to have: Google APIs (Sheets, Drive, BigQuery), workflow automation tools like n8n. AI-Assisted Development: Hands-on experience building with LLM tools and APIs (OpenAI, Claude/Anthropic, Cursor, Replit AI, or similar), and the judgment to evaluate, refactor, and productionize AI-generated code into a clean, maintainable stack.