Sr. Software Engineer – Backend

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