Backend Engineer · distributed systems, and the AI layer on top of them
I'm a backend engineer with 4+ years building distributed services in Go, Java and Node.js — the kind that move money, records and orders between systems that can't afford to lose them.
An increasing share of that work is putting LLMs into production rather than into demos: retrieval pipelines that cite their sources, MCP servers that give models real tools, and agentic workflows that replace multi-step manual processes.
Most recently that's meant national-scale infrastructure. At Wits Innovation Labs I architected the backend for an integration testing platform on India's ONDC network — thousands of organizations run their implementations against it before going live, across 20+ business domains. Before that, pension transaction systems and enterprise workflow orchestration.
Note
I like problems where correctness matters more than shipping speed, and where you find out quickly if you got it wrong.
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Microservices and event-driven architecture Kafka and RabbitMQ pipelines Distributed SQL and data consistency Fault tolerance under production load |
Production RAG pipelines with citations MCP servers exposing systems to any LLM Agentic multi-step workflows Vector search and embeddings |
Kubernetes on AWS and GCP CI/CD and observability API gateways, OAuth2 and JWT Cryptographic request signing |
| LANGUAGES |
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| BACKEND & APIS |
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| DATA & MESSAGING |
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| CLOUD & INFRA |
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| AI & LLM |
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| SECURITY |
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Open to backend and platform engineering roles — distributed systems, high-throughput infrastructure, or applied AI over real production data. Remote or hybrid.
