Principal Engineer / Architect (Node+Golang+React)

Job Description : We’re looking for a Principal Engineer / Architect – Full Stack with 8+ years of experience in building, architecting, and delivering scalable, high-performance web applications. The role requires deep expertise in Node.js, React.js, Go (Golang), and GraphQL, along with strong experience in system architecture, database design, and cloud-native deployments. The Ideal Candidate will lead technical strategy, ensure system reliability, and drive engineering excellence across teams.Role & Responsibilities : Architect and build scalable applications using Node.js , Golang , and React.jsDevelop and maintain high-performance APIs and microservices with GraphQL and Apollo .Create modern, reusable frontend components with React.js and TypeScript .Design and optimize PostgreSQL(or any other Sql) databasesImplement CI / CD pipelines , Terraform , and Kubernetes deployments on AWS / GCP .Ensure reliability through automated testing using Jest , Cypress , and Testing Library .Collaborate across teams on architecture , performance optimization , and best practices .Skills Required : 8+ years of hands-on experience in full-stack engineering , architecture , and system design .Expert proficiency in Node.js for scalable backend architecture.Deep experience with React.js and modern frontend development.Strong command of Go (Golang) for performant, distributed systems.In-depth knowledge of GraphQL and Apollo Client / Server for scalable APIs.Extensive experience with PostgreSQL (or any other Sql) databases.Advanced TypeScript / JavaScript expertise across the full stack.Strong focus on testing and code quality using Jest , Cypress , and Testing Library .Solid understanding of design principles and C4 modelling.Good to have Skills : Experience in building and maintaining scalable, maintainable solutions using React , React Native , and Express.js (or similar frameworks).Experience with Kafka for event-driven systems.Knowledge of Temporal for workflow orchestration.Proficiency with Docker and Kubernetes for containerized deployments.Working knowledge of Redis for caching and session management.Experience with DataDog or similar monitoring tools.Experience with AI frameworks like LangChain , LangGraph , and RAG pipelines .Exposure to OpenAI API for LLM-based application development.