Work With Me
I help teams build AI products that are useful beyond the demo.
I work at the intersection of product UX, backend workflows, RAG systems, agent control, LLM evaluation, deployment, and implementation-driven teaching.
Clear offers
Choose the outcome you need.
AI Product Architecture Review
Founders, product teams, and engineering leaders
A practical review of workflow, RAG/data path, agent boundaries, evals, observability, cost, latency, and rollout risk.
Book architecture reviewFull-Stack GenAI Workshop
Colleges, FDP programs, and engineering teams
A hands-on learning experience with diagrams, starter code, build tasks, project checkpoints, and evaluation guidance.
Invite me for workshopAI Engineering Mentorship
Students, early engineers, and software developers moving into AI
Portfolio review, project roadmap, learning path, implementation guidance, and interview preparation direction.
Discuss mentorshipFull-Time / Consulting Discussion
Hiring managers and teams building AI-enabled products
A focused discussion around role fit, system-building experience, project proof, and full-stack AI engineering scope.
Discuss role fitChoose your path
Different visitors need different proof.
For hiring managers
Problem: You need an engineer who can contribute across AI product UX, backend workflows, RAG, evaluation, and deployment.
What I can deliver: Full-stack AI engineering execution, architecture judgment, code ownership, and practical delivery across the product stack.
Relevant proof: Runnable flagship harness, case study, full-stack AI positioning essay, and proof wall.
Review proofFor founders and product teams
Problem: Your AI prototype works in demos but needs clearer architecture before production users depend on it.
What I can deliver: Architecture review across user workflow, data path, retrieval quality, agent boundaries, evals, cost, latency, and rollout risk.
Relevant proof: Agentic AI Production Harness, tool contracts, traces, golden workflow evals, and AI product risk framing.
Review proofFor colleges and workshop hosts
Problem: Learners and faculty need implementation-driven AI engineering training instead of passive theory.
What I can deliver: Hands-on sessions with diagrams, starter code, project tasks, evaluation checklists, GenAI app development, FDP sessions, and project review.
Relevant proof: SMVITM AICTE ATAL FDP proof, DSCE Full-Stack GenAI workshop proof, MIT Pune AI/ML workshop proof, and project-driven teaching assets.
Review proofFor mentoring and career support
Problem: Students and engineers need a path from programming and system design into practical AI engineering.
What I can deliver: Project planning, portfolio review, interview preparation, learning roadmap, and hands-on implementation guidance.
Relevant proof: 5,000+ learners and professionals mentored through sessions, workshops, and coaching.
Review proofWhat to send
- •What you are building, hiring for, or planning to teach
- •Current stage: idea, prototype, pilot, production, workshop, FDP, or mentoring need
- •Main challenge: product UX, backend workflow, RAG, agents, evals, cost, latency, deployment, or learning path
- •Expected outcome: role discussion, architecture review, workshop, faculty session, mentoring, or advisory
Review before contacting
Proof wall
Review workshops, technical projects, writing, and mentoring proof in one place.
Projects
Inspect flagship and full-stack AI project patterns.
Writing
Read technical notes and architecture thinking.
SMVITM FDP proof
See AICTE ATAL FDP certificate, classroom, and resource person proof.
DSCE workshop proof
See Full-Stack GenAI application development workshop and judging photos.
MIT Pune proof
See national-level AI & ML workshop photo evidence.
Runnable harness
Run the demo and eval suite on GitHub.