AI Engineer · Full-Stack Engineer · Applied Machine Learning
Designing and shipping scalable AI systems from idea to production
AI Engineer with strong software engineering fundamentals and hands-on experience building production-grade AI systems.
I specialize in LLM-powered applications, backend-heavy full-stack systems, and scalable cloud deployments.
Comfortable operating in ambiguous, fast-moving environments where ownership, correctness, and performance matter.
Current
- Building AI-driven automation for internal business workflows
- Designing LLM-powered systems with focus on reliability, cost, and latency
- Collaborating cross-functionally to translate product requirements into deployable AI solutions
Jan 2024 – Jul 2025 · 1 yr 7 mos
Stack: React · Astro · Node.js · Hono.js · MongoDB · Docker · AWS
- Architected and shipped a multi-tenant B2B e-commerce platform end-to-end
- Designed secure authentication & RBAC for buyers, sellers, and admins
- Built high-throughput backend services for catalogs, orders, and inventory
- Improved API and query performance by ~40% through indexing and query optimization
- Served as technical owner from system design to production deployment
- Mentored junior engineers; reviewed PRs and set engineering standards
AI / ML
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- NLP pipelines & embeddings
- Model training, evaluation, and inference
- Applied ML (notebooks → production)
Engineering
- Backend system design
- REST APIs & authentication
- Distributed systems fundamentals
- Dockerized services & cloud deployment (AWS)
- Performance optimization & observability
- Bachelor of Computer Applications (BCA) — Completed
- Master of Computer Applications (MCA) — In Progress
Roles where I can:
- Build real-world AI systems at scale
- Work on high-impact problems with strong engineering standards
- Learn from senior engineers and researchers
- Contribute to AI-first products or platforms
Open to AI Engineer, ML Engineer, Software Engineer (AI/ML) roles across:
- Big Tech / FAANG-level teams
- High-ownership startups
- Applied AI / research-oriented groups
Bias for action. Ownership over outcomes.
