SOURAV R.

I find and fix the problems in Go and PostgreSQL backends before your users do: data leaking between customers, double charges, lost retries, slow queries and risky migrations. I'm a senior backend engineer (SDE 3) at slice, a digital bank in India, where I lead the team behind the core payments platform. I built its transaction orchestration platform from zero; it now handles a few hundred million transactions a month across UPI, IMPS, NEFT and RTGS at 99.9% uptime. Before that I spent 3+ years building security and data platforms at FireEye (cloud SIEM, 1B+ events a day) and Query.AI. Integrated BTech + MTech in Mathematics & Computing, IIT (BHU). WHAT I DO FOR CLIENTS 1. Backend code and security review, fixed price. I map every route against every role, test tenant isolation, payment and webhook flows, and deliver a written report: each finding with the request, the code line, the impact and the fix, ranked by risk. Optional retest after you fix. 2. Payments and money-movement correctness: idempotency, retries, reconciliation, ledgers, webhooks, and what happens when a provider times out halfway. 3. PostgreSQL performance and zero-downtime change: schema design, query tuning, partitioning, migrations on live tables. 4. Building backend services in Go or Python: APIs, workflow orchestration, Kafka pipelines, third-party integrations, monitoring and alerting. PROOF - Transaction orchestration platform for a bank, built from scratch in Go: all payment modes, deposits and wallet flows - A Temporal-style durable workflow engine that survives crashes, retries and duplicate requests; new product workflows are built on it - Partitioned billion-row (2TB+) Postgres transaction tables on the live money path with no planned downtime (written up publicly) - Migrated millions of records between core banking systems with dual writes and reconciliation: zero validation failures - Rebuilt alerting: incident detection from 10 minutes to 1; penalty-hit failed transactions down ~85% - Infrastructure cost down ~40%; real-time risk checks cut fraud exposure 88% across 1M+ users - FireEye: rewrote an ML log-parsing system from Python to Go (41% faster). Query.AI: 15+ security vendor integrations (CrowdStrike, Palo Alto, SentinelOne) and a Splunk Marketplace app used by 10+ enterprise clients ON UPWORK $30K+ earned with 5.0 feedback, including a 615-hour engagement building Python security-automation integrations and SOAR playbooks. HOW I WORK Fixed price per deliverable, funded milestones, NDA on request. Written scope before I start and no surprises on cost. I verify every finding myself before it goes in a report. I'm on IST (UTC+5:30), with overlap with Europe, the Gulf and US mornings and evenings, and I reply within a few hours. Send me what you've built and what worries you about it. I'll reply with how I'd check it and a fixed price.