Senior Backend Engineer - Systems, Database & Performance

Location: Gurgaon

Experience: 6 - 12+ years

Company: Animall

About the role:

Animall builds technology products for Bharat, serving millions of users across cattle commerce, agriculture, livestock services, subscriptions, and other digital products.

We are looking for a deeply hands-on backend engineer who can own complex production systems and make them simpler, faster, more reliable, and easier to scale.

You'll often be given problems rather than detailed specifications. We expect you to independently investigate, design, implement, deploy, measure, and iterate.

What you'll own:

- Backend architecture and service design

- Database architecture, schema design, and query performance

- High-scale APIs and asynchronous systems

- Performance bottlenecks across application, database, cache, and infrastructure layers

- Reliability, observability, and production debugging

- Background jobs, queues, retries, idempotency, and concurrency

- Large-data migrations and zero/minimal-downtime schema changes

- Capacity planning and scaling systems as traffic and data grow

- Simplifying existing systems and reducing technical debt

- Improving engineering practices across the backend team

What we're looking for:

Backend & distributed systems:

Strong experience designing and operating production systems at meaningful scale, including APIs, distributed systems, asynchronous processing, queues, caching, concurrency, failure handling, rate limiting, backpressure, and pragmatic service design.

Deep database expertise:

Strong PostgreSQL and/or MySQL fundamentals including schema design, indexing, query optimization and execution plans, transactions, isolation levels, locks/deadlocks, connection pooling, replication, partitioning, migrations, pagination at scale, and data consistency.

Performance & production engineering:

Comfortable systematically debugging slow APIs, high DB load, memory/CPU issues, connection exhaustion, query regressions, p95/p99 latency, traffic spikes, hot rows/keys, slow background jobs, and infrastructure bottlenecks.

AI-native engineering:

Actively use modern AI coding and reasoning tools to improve speed and quality. Must have technical judgment to challenge AI output, detect bad assumptions, and validate correctness.

Engineering philosophy:

- Simple systems are usually better than clever systems.

- Measure before optimizing.

- Production behaviour matters more than architecture diagrams.

- Database knowledge is a superpower.

- Reliability is part of product quality.

- Good engineers reduce complexity.

- Senior engineers should own outcomes, not just tickets.

- AI should remove low-value engineering work.

What would make you stand out:

- Operated databases with hundreds of millions or billions of rows.

- Significantly reduced production latency or infrastructure cost.

- Diagnosed difficult concurrency or consistency bugs.

- Executed large production migrations safely.

- Built systems processing large volumes of asynchronous jobs/events.

- Materially improved reliability of a production system.

- Can explain a major production incident you personally debugged end to end.

- AI tools have changed the way you engineer.

What you'll get:

- High ownership

- Direct access to engineering and company leadership

- Real production systems and meaningful scale

- Fast decision-making

- Minimal process overhead

- Opportunity to shape architecture and engineering standards

- Ability to ship meaningful changes quickly

- A team that actively embraces AI-powered engineering

Interested?:

Send us your LinkedIn / GitHub / profile along with a short note covering:

- 2 - 3 technically difficult systems or problems you've personally owned

- A production or performance problem you're proud of solving

- How AI has changed the way you engineer