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. Main Responsibilities Define and maintain engineering standards, development guidelines, and code quality practices for the team Lead architecture decisions for the Internal Operational Platform and connected tooling Build and maintain full-stack applications using Java/Spring Boot and React/TypeScript Convert existing vibe-coded MVPs into production-ready implementations Refactor prototype logic into clean backend services, typed APIs, database schemas, and maintainable frontend workflows Design PostgreSQL schemas and Liquibase migrations Integrate BigQuery reads and adjusted publish layer Follow and enforce OpenAPI-first development and typed frontend API clients Own backend observability through Actuator, Prometheus metrics, and structured logs Ensure apps are deployable, maintainable, and ready for engineering handoff Work with business stakeholders to preserve product intent while raising technical quality Backend Must-have: Java 21 Spring Boot 3.x Maven REST API design + OpenAPI contract-first development PostgreSQL schema design Liquibase Spring Security Actuator metrics, Prometheus, structured backend logs Strong preference: Experience with multi-module Maven projects Experience integrating legacy systems without rewriting them Experience defining backend architecture standards and code review practices Frontend React + TypeScript Vite API-driven UI TanStack Query or equivalent server-state management Strong handling of loading/error/empty states Ability to build practical workflow UIs, not just static pages Data / Integration Must-have: BigQuery or similar warehouse experience Understanding of versioned data, published views, and source-of-truth boundaries Ability to reason about data freshness, cache rebuilds, and fallback behavior Nice-to-have: Google APIs: Sheets, Drive, BigQuery n8n or workflow automation AI-Assisted Development Must-have: Hands-on experience with AI-assisted development and LLM integrations, including tools and APIs such as OpenAI, Claude/Anthropic, Cursor, Replit AI, or similar Ability to evaluate, refactor, and productionize AI-generated or vibe-coded applications into a maintainable stack with clear architecture, typed APIs, proper auth, persistence, observability, and deployment practices