Final-year B.Tech at NIT Hamirpur (2026). Building at the intersection of intelligent systems, security, and data — code that scales, systems that last.
I engineer systems that are fast, secure, and built to understand data at scale.
Final year B.Tech at NIT Hamirpur (Tier-1 NIT, 2026). I build across three domains — software, security, and data — tying them into production-grade intelligent solutions.
I integrate OpenAI, Anthropic Claude, and LangChain into high-throughput FastAPI backends, instrument them with Prometheus & Grafana, and ship everything via Docker + Kubernetes.
Beyond code, I've led a 50+ member engineering team, hold certs from DeepLearning.AI, and use Claude Code + Cursor daily.
Each domain is something I actively build in — together they form a unique profile connecting systems, security, and intelligence.
Scalable APIs, microservices, and AI-integrated systems built for real production traffic.
From threat modelling to penetration testing — understanding systems by trying to break them.
Statistical rigour meets ML engineering — models that actually perform in production.
Every tool here is something I've shipped code with.
Production AI backends and orchestration pipelines.
Offensive & defensive across web and network layers.
From EDA to production model deployment.
Infrastructure keeping AI systems running.
AI-native dev with cloud tooling.
Full-stack capabilities when context matters.
Real systems — LLM orchestration to security tools and data pipelines.
AI/ML · Production
Multi-provider LLM gateway with routing, fallback logic, token budgeting, and full observability behind a unified FastAPI interface.
Cybersecurity · Python
Custom OWASP Top 10 scanner detecting SQLi, XSS, IDOR, and misconfigured headers. Generates structured reports with severity scoring.
Data Science · LLM
Enterprise document Q&A using retrieval-augmented generation. Ingests PDFs, indexes via vector embeddings, answers with grounded citations.
Cybersecurity · Data Science
ML-based IDS classifying network attacks in real time with Random Forest + Gradient Boosting ensemble — deployed as a FastAPI microservice.
Infrastructure · Observability
End-to-end ML system monitoring tracking inference latency, token usage, model drift, and API errors with Grafana dashboards.
Cybersecurity · Data Engineering
Automated ETL pipeline ingesting CVE feeds, threat intel APIs, and OSINT sources — normalises and surfaces high-priority threats.
Leadership and engineering roles that shaped how I think about systems.
Open to AI/ML roles, cybersecurity collaborations, and data science projects. Remote preferred — PST overlap available.