Kumar Harsh

Software Engineer

Bengaluru, Karnataka, India0 mo experience

AI EnabledAI ML Practitioner

Key Highlights

Hands-on experience in scalable backend services.
Proven ability to optimize system performance.
Strong background in API development and microservices.

Stackforce AI infers this person is a Backend-focused Software Engineer with expertise in SaaS and microservices architecture.

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Skills

Core Skills

FastapiPython (programming Language)React

Other Skills

JWTRedisJavaScriptMemoizationGoogle GeminiJSON Web Token (JWT)MicroservicesJob AnalysisCode ReviewLeaflet.jsGoogle Maps APICode RefactoringProtocol AnalyzerWAMPApplication Development

About

Software Engineer Intern with hands-on experience building scalable backend services and performance-focused web applications, with a strong background in API development, microservices-based systems, and database-driven applications. Proven ability to debug production issues, optimize system performance, and collaborate across thestack to deliver reliable, production-ready solutions.

Experience

0 mo

Total Experience

Average Tenure

Current Experience

Aura cloud

Software Engineer Internship

Mar 2026 – Present · 3 mos · Bengaluru, Karnataka, India · On-site

Python (Programming Language)FastAPI

Cloudifyjob

Software Engineer Intern

Dec 2025 – Mar 2026 · 3 mos

Developed FastAPI-based microservices behind a centralized API gateway to enable scalable inter-service communication and improve overall system reliability.
Integrated JWT-based authentication and applied Redis caching to reduce redundant database queries and improve API response times by 30%.
Architected secure RESTful APIs with robust request validation, structured error handling, and standardized HTTP responses to ensure consistent and stable backend behavior.
Engineered scalable React interfaces using functional components, Context API, and custom hooks to promote reusable logic and predictable lifecycle management.
Optimized frontend performance by minimizing unnecessary re-renders through memoization, efficient state handling, and hook refinements, achieving a 45% faster load time.