Aashish Kumar

Backend Engineer

Ex-Software Developer Intern @Webability

Ex-Backend Developer Intern @Zeepty Technologies ltd.

Ex-Software Developer Intern @Aky Deva

About

Backend-focused engineer specializing in Golang, Node.js and Distributed systems, building production-grade services designed for scalability, reliability, and fault tolerance from the ground up.
Designed high-throughput systems processing 30K+ daily jobs and 10K+ events/min, implementing transactional outbox, visibility timeouts, DLQs, bounded retries, and idempotent workflows to guarantee reliability under failure.
Strong hands-on experience with Concurrency in Go — worker pools, goroutines, channels, mutex, semaphores, backpressure handling, and graceful shutdown using contexts.
Strong believer in designing for failure first — crash resilience, zero job loss guarantees, at-least-once delivery semantics, and database-safe concurrency patterns.
Cloud & DevOps aware engineer with practical experience in Docker, Kubernetes, AWS, and CI/CD pipelines, focusing on reproducible builds, automated testing, and production-ready deployments.
Currently advancing my expertise in Observability Engineering, Testing, Benchmarking, and Profiling, ensuring systems are not just functional but measurable, optimized, and performance-conscious.
Built Monit — a distributed uptime monitoring system can handle 1M+ monitors.
Built Outflow — a crash-resilient transactional outbox processor handling 10K+ events/min.

Architected a distributed website auditing system using Go, Node.js and RabbitMQ with 30+ checks, processing 30K+ webpages/day via horizontally scalable crawler–queue–worker architecture.
Designed fault-tolerant job processing workflows with bounded retries, re-queuing, and DLQs, reducing job failures rate from 30% to <5% under worker crashes.
Introduced Redis-backed job state tracking and result caching, cutting database calls by ~10–15× and eliminating high-frequency polling, improving responsiveness and preventing DB bottlenecks under load.
Enhanced system observability and stability by implementing structured Zerolog logging and standardized Go error-handling patterns, making production failures easier to trace and reducing diagnosis time by ~2 times.

Developed a production Go service integrating with YouTube APIs using OAuth 2.0, building 15+ RESTful APIs with Chi router and MVC architecture to automate creator workflows and improving efficiency
Engineered a horizontally scalable Go worker service, processing SQS events concurrently using worker pool patterns, channels, and contexts, enabling parallel processing, graceful shutdown, and improved system stability under load.
Integrated CI/CD pipelines using GitHub Actions for 5+ Microservices with optimized Docker builds, automating testing and deployment workflows and reducing hours of manual effort to minutes per release.