Praveen Kumar logoPraveen Kumar

Work With Me

I help teams build AI products that are useful beyond the demo.

I am focused on full-stack AI engineering: product interfaces, backend workflows, RAG systems, agentic AI, LLM evaluation, deployment, and mentoring.

Reach out on LinkedInBook a meeting

Choose 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, and full-stack AI positioning essay.

Review proof

For 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, and golden workflow evals.

Review proof

For 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 proof

For 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 proof

What 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

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.