Ayush Kumar Anand

00:00

he/him

About

Backend and distributed systems engineer focused on building reliable, scalable, and performance-oriented infrastructure.
Built distributed systems from first principles, including a Raft-based key-value store and a GFS-inspired distributed file system with replication, consistency, crash recovery, and fault handling.
Experienced in designing high-concurrency APIs, asynchronous workers, caching layers, real-time systems, and data pipelines using Go, Python, TypeScript, Redis, PostgreSQL, and MongoDB.
Built DevBrain, an engineering-memory platform that transforms GitHub commits, PRs, issues, ADRs, and code structure into a hybrid graph-vector knowledge layer for software teams.
Comfortable working across backend, cloud, observability, and frontend systems, with hands-on experience using Docker, Kubernetes, AWS, Azure, Prometheus, and Grafana.
Active open-source contributor with contributions to projects including Zed, and Talawa.
Smart India Hackathon 2024 Runner Up, Odoo Hackathon Grand Finalist, Amazon ML Challenge Top 0.25%, and Grand AI Challenge Stage 1 Winner.

753 contributions in 2025 on GitHub.

LessMore

Reduced cold-search latency by ~50–70% (25–90s → 8–25s) through parallelized multi-source API calls, Redis caching, and stale-while-revalidate.
Migrated compute-heavy trend generation to Redis-backed ARQ workers, eliminating up to 90s of blocking API execution and serving cached results in <50ms.
Improved prediction-scoring correctness by eliminating a +367% false-growth bias on flat trends and restoring the acceleration signal in model confidence.
Productionized TrendSeer on AWS using EC2, S3, Systems Manager, Secrets Manager, and GitHub Actions with automated deployments, rollback checks, hourly uptime monitoring, and daily MongoDB backups.