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Roles: SDE-3 or Tech Lead Engineer
Experience: 6-9 years
Location: Bangalore

About ANAROCK and myHQ
At myHQ, we’re reimagining how India works. We are building India’s largest marketplace platform for flexible workspaces helping individuals and teams across 25+ cities find workspaces that just work.

We’re a small, product-first team backed by ANAROCK, moving fast and solving real engineering problems at scale. This is where you’ll get to own systems end-to-end, not just push tickets.

About the role
We’re looking for a Backend Technical Lead who can own the engineering vision for the platform end-to-end. This role is equal parts technical leadership, system & platform designs, and people management.

You will define our engineering roadmap, raise the bar on architecture, improve developer productivity (increasingly with AI in the everyday development loop), mentor engineers, and ensure high-quality sprint delivery.
This is ideal for someone who thinks in systems and enjoys combining hands-on coding with leadership.

Key Responsibilities
  • Own architecture end-to-end: design, build, and scale systems
  • Set the long-term technical direction.
  • Lead initiatives around performance, security, observability, and platform reliability.
  • Set standards for testing and code quality that hold up when a large share of code is agent-written.
  • Drive adoption of engineering best practices and new tooling across the org.
  • Mentor and lead engineers in the team
  • Own sprint planning, estimations, and delivery for engineering workstreams.
  • Ensure predictable execution while balancing short-term needs with long-term tech health.
Desired Skills/ Experience
  • 6 - 9 years building production-grade systems at scale.
  • Expertise in least one backend framework or language
  • Strong data modelling in both relational and document databases, and the judgment to know which one a problem wants.
  • Fluency in the fundamentals: caching, queues and async work, idempotency, read scaling, concurrency and connection limits, and an accurate mental model of how database perform under load.
  • Ability to lead technical discussions, make trade-offs, and guide teams through ambiguity.
  • Experience improving developer productivity through tooling, process, or automation
  • Comfort building product surfaces on top of LLMs - retrieval, structured extraction, evaluating output quality.
  • Experience leading an engineering team or mentoring senior engineers.
Nice to have
  • Worked at an mid-stage startup.
  • Experience with eCommerce, Marketplace, discovery, search or geospatial systems.
  • Event-driven architecture and message queues at scale.
  • Working effectively with AI coding agents: the scaffolding, tests and conventions that let them ship safely rather than just quickly.
People & Culture
  • Freedom to execute,  an open culture with passionate and smart co-workers
  • Performance oriented team driven by ownership and open to experimentation
  • New tooling, AI included, gets tried early rather than debated at length
  • Lean, fast-moving team where engineers own critical systems end-to-end.
Other Perks / Benefits
  • Comprehensive term and health insurance for you and your dependents
  • Paid maternity / paternity leave to let you spend valuable time with your loved ones
  • Learning budget
  • AI / LLM tooling for every engineer, and the room to actually use it
Frequently Asked Questions
What’s the interview process like?
The interview process consists of 3-4 rounds of technical discussion of 60 mins each and a 30 min cultural fitment discussion. The technical discussion rounds cover past projects, programming basics, DS / Algo and system design. This is followed by a 30 min cultural fitment round.
What’s the technical stack that you’re working on?
Our tech stack is built on
    • Core platform: Node.js and Express, layered service architecture, MongoDB with Mongoose
    • Newer services: TypeScript on Node, PostgreSQL with pgvector, Prisma
    • Async and caching: Redis, BullMQ, change streams, Elasticsearch
    • Infrastructure: DigitalOcean and AWS, nginx, PM2, Lambda for isolated services
    • Observability: Sentry, Elastic APM and Kibana, CloudWatch
    • Testing: Mocha, Chai and Sinon on the core platform, Vitest on newer services
    • Clients: React, Angular with Capacitor, Next.js, served through BFFs
    • AI: LLM APIs behind product surfaces, embeddings and vector search on pgvector, evals in the release loop, and coding agents in the daily workflow

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