About

Java and backend engineer with independent product ownership.

I am Harsh Srivastava, a backend engineer based in Bengaluru. My work focuses on high-throughput systems, production reliability, clearly defined product requirements, and measurable engineering outcomes.

Professional summary

Enterprise backend systems and independently developed products.

My professional work covers Java backend engineering, event-driven data processing, cloud delivery, and production operations. Independently, I build products where the architecture has to support a real workflow, not just a demo path.

I am most useful where product requirements, backend architecture, and production behavior meet: data movement, failure handling, observability, latency, and operational clarity.

Bengaluru, India B.Tech CSE, VITLeetCode
Preview of Harsh Srivastava's Java backend engineer resume

Resume

Harsh Srivastava · Java and Backend Engineer

Education

Vellore Institute of Technology

B.Tech in Computer Science and Engineering, Business Systems

2020 — 2024Program duration
8.4GPA

Technical skills

Backend, distributed systems, cloud, observability, and AI engineering first.

The inventory keeps primary engineering strengths visible first, while project-specific libraries remain available without being presented as equal to Java, Spring Boot, Kafka, AWS, or Kubernetes.

Java and backend engineering

Java
Spring Boot
Node.js
TypeScript
JavaScript
Python
GraphQL
REST APIs
gRPC
Microservices
FastAPI
Flask

Data and distributed systems

PostgreSQL
MySQL
Oracle Database
IBM DB2
Cassandra
Redis
Kafka
Apache Avro
Supabase
Prisma
SQL
Concurrency
Bounded parallelism
Retry mechanisms
Failure isolation
Caching

Cloud and delivery

AWS
EC2
S3
IAM
Aurora
Kubernetes
Docker
Jenkins
ArgoCD
Terraform
GitHub Actions
CI/CD
Vercel
Railway

Testing and observability

Prometheus
Grafana
Playwright
k6
API tracing
SQL debugging
Production debugging
Log forensics
Kafka flow inspection
Kubernetes pod debugging
Schema validation
TLS
Jest
pytest
Vitest

AI engineering and developer tooling

OpenAI
OpenAI Codex
Claude
Claude Code
Anthropic
DeepSeek
MiniMax
MiniMax M3
Kimi
Azure OpenAI
Presidio
tiktoken
Structured-output validation
Evaluation pipelines
Red-team evaluation
Benchmark dashboards

Product-development skills

Next.js
React
Material UI
Tailwind CSS
shadcn/ui
Auth.js
Cashfree
Google OAuth
GitHub OAuth
Resend
Cloudflare Workers
Recharts

Additional tools used across projects

Bootstrap
Cheerio
Cobra
Create React App
CSS
DNS
E2B
Emotion
ESLint
Framer Motion
Git
GitHub Pages
Go
Google Analytics
Google Search Console
GoReleaser
Gunicorn
Heroku
Homebrew
HTML
html2canvas
HTTP
Jinja
jQuery
jsPDF
Lip Gloss
Lucide
MDX
Microsoft Clarity
Neon
npm
NVIDIA
OMDb
Plausible
PostCSS
Pydantic
PyPI
Redpanda
Render
Sharp
SQLAlchemy
SQLite
styled-components
TCP
Temporal
Testing Library
Upstash Redis
Vercel Analytics
Vercel Speed Insights
YAML
Zeroconf
Zod

Engineering principles

Priorities applied across the work.

01

Defined utility

Each product should improve a specific task through clearer, faster, or safer execution.

02

Evidence-based evaluation

Metrics, tests, logs, and explicit limitations provide the basis for technical claims.

03

Operational completeness

Deployment, observability, failure handling, and recovery are treated as core system requirements.