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Harsh Kumar

Junior Full-Stack Engineer specializing in web apps, cloud services, and data migrations

MindSpark VenturesArizona State UniversityRemote1 Years ExperienceJunior LevelWorks On-Site

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About

Built SparkyAI, a gamified college-essay writing assistant (hackathon project at ASU in 2025) using React/styled-components, Firebase (OAuth/DB), and OpenAI APIs, with concrete scalability and performance measures like rate limiting, indexed queries, code splitting, and conversation caching. Also designed a global low-latency voice-to-LLM architecture leveraging WebRTC, regional containerized services, global load balancing, streaming STT/TTS, and end-to-end encryption with minimal logging.

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Key Strengths

  • Full-stack delivery using React + Firebase + OpenAI API
  • Scalability planning with managed infrastructure and tier-based scaling (Firebase/OpenAI)
  • Abuse prevention via rate limiting (10 responses/min) and malicious-input validation
  • Performance optimization: reduced JS bundle size and implemented code splitting
  • Database performance tuning with indexed queries in Firebase
  • LLM context management via caching last 10 conversational messages
  • Systems thinking for low-latency global voice+LLM architecture (WebRTC, regional containers, global load balancing, streaming STT/TTS)
  • Cross-functional collaboration with non-engineers using weekly demos and frequent status updates

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Experience

Systems EngineerMindSpark Ventures · Oct 2025 – Present
Frontend DeveloperMindSpark Ventures · Aug 2025 – Oct 2025
Full-Stack Engineer InternVelocity Tech Inc. · Jan 2024 – Dec 2024internship
Section LeaderStanford University · Apr 2025 – Jun 2025
Technical DirectorSoftware Developer’s Association · Jan 2022 – Dec 2022

Education

Arizona State Universitybachelor, Computer Science (2025)

Awards

  • Moeur Award Recipient - Arizona State University
  • Dean’s List (eight semesters) - Arizona State University

Languages

English

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Harsh KumarJunior Full-Stack Engineer specializing in web apps, cloud services, and data migrations