Lead Full Stack Engineer (MERN/MEVN) | 5–12 Years Experience | 20 LPA

About the Role
You will lead the next stage of the core product as the company scales a working, customer-used MVP across India. As the first technical leader, you will write code, own architecture and help other engineers do their best work. This is a hands-on role focused on the existing product, with direct access to the founders and real influence over engineering practices and hiring.
What You Will Own
- Scale with purpose: Prepare the platform for 10x load through targeted refactoring, performance work and sound architectural choices, while keeping delivery on track.
- Own reliability: Set up observability, alerting, on-call practices and incident response so the team finds problems before customers report them.
- Raise delivery standards: Build practical approaches to branching, code review, testing and CI/CD, including dependable deployment and rollback.
- Enable applied AI: Partner with the AI engineering team on product features, owning the surrounding architecture, reliability, latency and cost.
- Protect product coherence: Turn customer needs into reusable capabilities and push back on changes that would fragment the core product.
- Develop the team: Mentor engineers, strengthen technical judgment and help define the hiring bar for the next stage.
The Focus
This is a long-term, hands-on engineering path covering coding, architecture and technical mentorship. Full-time people management and AI research are outside the main scope.
What You Bring
- Experience: 7 to 10 years in engineering, including 2+ years as the most senior engineer on a team, with a track record of scaling an existing product without stopping delivery.
- Stack: Strong hands-on experience with MERN or MEVN (MongoDB, Express, React or Vue, Node.js).
- Distributed systems: Horizontal scaling, caching, queues, background jobs, asynchronous and event-driven design, idempotency, rate limiting, graceful degradation and load testing.
- Data performance: Schema and index design, query optimisation and zero-downtime migrations on live customer data.
- Cloud architecture: Designing and running production systems on AWS, and weighing containers versus serverless and synchronous versus queue-backed execution with clear cost and complexity trade-offs.
- Production ownership: Provisioning, scaling, monitoring, live debugging and incident response, with strong judgment about what to build and what to leave out.
- Security and efficiency: Authentication, authorisation, customer data isolation, and control of cloud and AI costs as usage grows.

Work arrangement
No