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Amar Singh

Amar Singh

Software Engineer Intern

Talent
HyderabadMember since August 19, 2026
PythonTypeScriptSQLNext.jsNode.jsFastAPIPostgreSQLRedisElasticsearchKubernetesRAGMCPMicroservicesSystem Design
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PythonTypeScriptSQLNext.jsNode.js

About

Hardened production reliability by optimizing Kubernetes container startup reducing cold-start latency by ∼70% (20s → 5s) and restructured logging to surface root-cause failures over downstream noise, halving debugging time. Benchmarked the MCP server powering LLM coding agents on cross-repository code retrieval by building a Python A/B evaluation harness (MCP-augmented vs vanilla), scoring retrieval accuracy across 50+ golden queries.

Experience

Software Engineer Intern at ByteBell (2026-06 – 2026-07)

  • Hardened production reliability by optimizing Kubernetes container startup reducing cold-start latency by ∼70% (20s → 5s) and restructured logging to surface root-cause failures over downstream noise, halving debugging time.
  • Benchmarked the MCP server powering LLM coding agents on cross-repository code retrieval by building a Python A/B evaluation harness (MCP-augmented vs vanilla), scoring retrieval accuracy across 50+ golden queries.

R&D Intern at Dtyle.AI (2025-07 – 2025-08)

  • Optimized high API latency under peak traffic by implementing Redis caching with invalidation strategies and optimized database indexing, reducing avg latency from 420ms to 270ms and increasing throughput from 75 to 110 requests/second.
  • Resolved inconsistent RESTful API behavior across 15+ endpoints by redesigning services in Node.js & Express, implementing centralized request validation and JWT authentication middleware, reducing client-reported errors by 38%.

Backend Developer Intern at SmartScore (2025-05 – 2025-06)

  • Scaled document processing bottlenecks under peak traffic (∼1200 requests/hour) by scaling Node.js services with non-blocking async workflows & tuning concurrency limits, increasing throughput by 45% and reducing timeout errors by 32%.
  • Reduced slow queries performance caused by growing data volume by designing normalized PostgreSQL schemas with composite indexes and optimized query plans, lowering average query time from 180ms to 95ms.

Education

BTech in Computer Science with Specialization in AI & ML – Vellore Institute of Technology (2023 – 2027)

Skills

Software Engineer Intern

Reviews

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