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  • India
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officialasishkumar/README.md

Asish Kumar

Backend & Infrastructure Engineer - Go, Kubernetes, Kafka, Observability

Hyderabad, India (IST) | Available for 20 hours/week | USD 55/hour

I work on Go backends and Kubernetes infrastructure for distributed systems. My current scope includes backend ownership for an enterprise AI training-data catalog and work on Kafka, PostgreSQL, and asynchronous-worker orchestration for automated AI evaluation pipelines. My current employer is not named on freelance-facing material.

Previously at Keploy, I worked on MongoDB wire-protocol mocking in Go against the raw binary protocol, Kubernetes record/replay across gRPC, PostgreSQL, MongoDB, Redis, Kafka, MySQL, and HTTP, eBPF traffic capture, and the backend for AI-driven Java unit-test generation used through a VS Code extension with 1.2M+ installs.

Selected work

Self-hostable LLM cost tracking with a multi-tenant Go and ClickHouse backend plus Go, Python, and TypeScript SDKs.

Multi-tenant event ingestion using Kafka, a PostgreSQL outbox, S3/SQS, Prometheus, Grafana, and Kubernetes deployment assets.

Asynchronous video narration using RabbitMQ, Redis, and FFmpeg.

Systems I work on

Go services and workers; Kubernetes internals; Helm; eBPF; Docker; Kafka; RabbitMQ; Redis; PostgreSQL; MySQL; ClickHouse; DynamoDB; Celery; S3/SQS; ArgoCD; Flux; OpenTelemetry; Prometheus; Grafana; gRPC; TLS/mTLS; JWT; rate limiting; consistent hashing; multi-tenancy; outbox delivery and replay.

Open source and programs

150+ merged pull requests across Apache, CNCF, Keycloak, Electron, cadence-workflow, kcl-lang/kpm, and visgl. Google Summer of Code with CHAOSS (2025) and TARDIS-SN (2024). Linux Foundation mentorship at KCL Language.

Contact

I take backend and infrastructure work, not generalist web-development work. Projects that overlap with AI training-data or post-training services require a conflict check before discussion.

Pinned Loading

  1. keploy/keploy keploy/keploy Public

    Open-source platform for creating safe, isolated production sandboxes for API, integration, and E2E testing.

    Go 18.4k 2.3k

  2. training-pipeline training-pipeline Public

    Logs-to-training pipeline for agentic LLM setups: ingest, redact PII, tag trajectories, export SFT (LoRA) and DPO datasets

    Python