Senior Software Engineer — Go (Trading Systems)

About the role

You will work on the backend of a retail trading platform carrying live order flow to NSE, BSE and MCX. The work spans order management, pre-trade risk, exchange connectivity and real-time market-data distribution — systems where correctness is non-negotiable, load peaks are unforgiving, and latency is measured in microseconds. You will own services in that path end to end.

Our stack: Go (primary), C#, PostgreSQL, MSSQL, Kafka, Redis, Aerospike, and in-house binary/TCP protocols.

Responsibilities

•Design, build and own Go services in the trading path — from design doc to production and on-call.

•Write concurrent code that is correct under load: goroutines, channels, select, and Go’s synchronisation primitives, used deliberately rather than by habit.

•Profile and optimise: pprof, benchmarks, escape analysis, allocation and GC pressure, lock contention.

•Build and consume TCP/binary and REST/WebSocket interfaces; handle partial reads, backpressure and reconnection properly.

•Write unit and integration tests; treat production incidents in your service as your problem to fix and prevent.

•Mentor junior engineers and raise the bar in design and code review.

•Work with QA, DevOps and Business teams through release cycles in a SEBI-regulated environment — auditability, change control, no shortcuts.

Must-have

•4+ years building production backend systems, with substantial recent Go.

•Deep grasp of concurrency: race conditions, deadlocks, memory visibility — and how to test for them.

•Capital markets domain: equity and F&O workflows, order types, margins, and how an OMS behaves.

•Hands-on with exchange connectivity or real-time market data in an Indian broking or trading environment.

•Strong SQL (PostgreSQL or SQL Server) and query performance tuning.

•Networking fundamentals: TCP vs UDP, sockets, timeouts, keepalives, framing.

•Complexity analysis applied to real design decisions.

•Git.

Good to have

•Distributed systems at scale: Kafka, Redis, Aerospike, or similar.

•Protocol buffers or other binary serialisation.

•Low-latency tuning experience — kernel, NIC, or GC-level.

•Effective use of AI coding assistants within enterprise data-handling norms.

Why this team

•Real ownership: you own a service end to end, not a ticket queue.

•Systems where performance engineering actually matters and is measured.

•Direct exposure to capital markets — domain knowledge that compounds over a career.

Hiring process

1. Screening call
2. Go and concurrency round (hands-on)
3. Systems design / problem-solving round
4. Discussion with engineering leadership