Shyam Sunder Singh

Backend Engineer

Hyderabad, Telangana, India1 yr 11 mos experience

Key Highlights

Expert in building reliable backend systems.
Proficient in Python and Go for real-time applications.
Focus on user impact and system stability.

Stackforce AI infers this person is a Backend Engineer specializing in real-time systems for SaaS applications.

Contact

singhshyam1089@gmail.com LinkedIn

Skills

Core Skills

Backend Web DevelopmentApi Development

Other Skills

PythonGoMySQLRedisCeleryAmazon Web Services (AWS)Software DesignStartupsJSONWeb ApplicationsApplication DevelopmentProgramming LanguagesData StructuresDatabasesC++

About

Backend engineer who builds systems for the real world, not just clean demos. I work across Python and Go, designing APIs and backend services that stay fast and sane when live data, concurrency, and unpredictable users show up. My bias is simple, stabilise what exists, remove pain points, then optimise until production stops crying. If users notice a bug, I already failed. I have worked on real-time and distributed traffic platforms running across hundreds of live locations. The details change, the problems repeat, latency beats features, logs beat dashboards, and systems should self-heal before humans wake up. Now I’m leaning deeper into backend design, real-time pipelines, and distributed data, where reliability matters more than syntax. Prefer production-first iteration over perfect abstraction, and I optimise only what users or logs complain about.

Experience

1 yr 11 mos

Total Experience

1 yr 11 mos

Average Tenure

1 yr 11 mos

Current Experience

Its planners and engineers

Associate Software Engineer

Jun 2024 – Present · 1 yr 11 mos · Hyderabad, Telangana, India · On-site

Backend engineering across Python and Go systems handling real-time data, high concurrency, and latency-sensitive operations deployed across live environments.
● Stabilised and extended existing backend services with incremental refactors rather than rewrites
● Built and tuned low-latency TCP and API services reaching very high concurrency in production
● Designed async pipelines using Celery, Redis and queuing patterns to move data reliably
● Integrated caching + datastore layers (Redis, Memcached, MySQL) to reduce load and improve response time under real traffic conditions
● Implemented monitoring and fault patterns that reduced human intervention and manual escalations
● Delivered features that improved user impact metrics (less delay, smoother flow) without breaking running systems
● Systems currently support live deployments across hundreds of intersections without outages impacting end users