Generative AI · LLMs · MLOps · Production AI

Hi — I’m Pramod Barkade.
AI Engineer with 10+ years building production AI systems — tutor and mentor to 1000+ learners.

I design and ship production AI: foundation model integration, retrieval-augmented systems, MLOps pipelines, and responsible AI practices. I teach by doing — hands-on labs, reproducible code, and mentorship that leads to real outcomes.

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10+ yrsIndustry & production AI
1000+Learners trained
50+Projects & deployments
Generative AI
LLMs & RAG
Prompt Engineering
MLOps & CI/CD
Responsible AI
AWS • Copilot • Gemini concepts
Quick learner • Motivator • Educator • Tutor • Mentor • Practical problem solver

About

Applied AI, product-focused engineering and learner-first training

I'm an AI Engineer and Educator with over a decade of experience building product-ready AI systems. I help individuals and teams move from prototypes to production, and mentor learners to ship real projects they can showcase.

Focus areas
LLMs, Generative AI, RAG, Vector DBs, MLOps, prompt engineering, and model evaluation.
Teaching
1:1 tutoring, group workshops, mock interviews, code reviews and project mentorship.
Values
Practical learning, reproducibility, ethics-first, and continuous sharing of knowledge.

Learn • Share • Grow

A practical cycle I follow with learners & teams

Prepare — curated materials and reproducible notebooks so every learner starts from a strong foundation.

Learn — hands-on workshops and guided projects with measurable outcomes.

Share — code, notes and templates are shared openly so learners can reference and reuse.

Grow — learners teach others, contribute to demos, and iterate on projects to build real impact.

Industry Trends & Guidance

What matters to engineering teams and learners
  • Model-Product Integration: RAG, caching, routing and measurement of end-user impact.
  • MLOps maturity: reproducible pipelines, monitoring, drift alerts and governance.
  • Cost-conscious serving: model routing, mixed precision and autoscaling patterns.
  • Responsible AI: bias audits, data handling, PII management and model cards.

Workshops & Courses

Structured, outcome-driven programs

LLM Foundations (Course)

10 modules: LLM basics, prompt engineering, evaluation, safety & a capstone mini project.
Outcome: deployable RAG demo + project report.

Production MLOps Bootcamp

Hands-on pipeline design, CI/CD for models, monitoring and cost optimization over 3 days.
Outcome: production-ready pipeline + runbook.

1:1 Mentorship (Project)

Custom mentorship with weekly reviews, code feedback and interview prep.
Outcome: portfolio-ready project and mock interviews.

Selected Projects & Case Studies

Production-grade systems & demo artifacts

My AI Mitra — Multimodal Language Assistant

Speech + text assistant across Indian languages using LLMs + RAG, monitoring, and cost playbook.

Conversational AI — Enterprise Support

Secure multi-turn assistant integrated with ticketing systems, with latency & safety engineering.

Model Ops & Deployment Platform

Reusable pipelines, A/B testing, canary rollout patterns and governance checklists.

Open-source LLM Demo Suite

Reproducible notebooks, tutorials and CI tests for learners to clone and extend.

Adaptive Learning Prototype

Personalised exercises, scoring rubrics and progress tracking for learners.

Cost-Optimized Inference Pipelines

Mixed-precision serving, batching, caching and model routing strategies for cost control.

Clients & Partners

Placeholders — replace with real logos when you have permission
Acme Labs
BrightLearn
FinEdge Solutions
HealthBridge
RetailWorks

Reviews & Testimonials

Feedback from learners, engineers and product teams
EL
Engineering Lead — Acme Labs
"Workshop and hands-on labs helped our team move from prototype to production quickly."
ML
ML Engineer — BrightLearn
"Mentorship was practical and focused — project guidance was invaluable."

Experience — AI Industry

Detailed roles, achievements and impact

Senior ML Engineer

2023 — Present · Leading cross-functional ML initiatives, designing and deploying production-ready AI/ML solutions. Responsible for CI/CD pipelines for models, monitoring, drift detection, and mentoring engineers and learners.

AI Consultant

2021 — Present · Delivered 20+ production AI projects across domains. Designed scalable MLOps platforms and conducted hands-on workshops for engineering teams. Key achievements include reducing inference costs by up to 40% and building multilingual RAG pipelines.

Senior Software Engineer / Tech Lead

2017 — 2021 · Led backend and ML-focused engineering teams, owned system design and deployment workflows, and implemented CI/CD practices. Actively mentored engineers and collaborated with product teams to deliver scalable, high-impact solutions.

Software Engineer

2015 — 2017 · Worked on full-stack and backend development, API design, and performance optimization. Contributed to core product architecture, internal tools, and engineering best practices.

Metrics & Impact

A snapshot of measurable outcomes
1000+ Learners
50+ Projects
40% Cost Drop (case study)
20+ Workshops

Publications & Resources

Guides, notebooks and repos I share
  • LLM Quickstart Notebook — reproducible notebook covering RAG, embeddings, and simple deployment.
  • MLOps Runbook — checklist for production model launches, monitoring and rollback strategies.
  • Prompt Engineering Notes — practical patterns and pitfalls for designing prompts and tool use.

Hiring & Skills Guidance

Advice for learners and hiring teams
  • For learners: 2–3 deployable projects, clear documentation of decisions and evaluation metrics.
  • For teams: Prioritise reproducible pipelines and monitoring before scaling model complexity.
  • Interview focus: system design for AI features, debugging & evaluation, and practical coding fluency.

FAQ

Common questions
Do your trainings include responsible/legal AI topics?+
Yes — modules on data privacy, bias audits, model cards and safe deployment practices. This is educational content and not legal advice; for contracts or compliance, consult your legal team.
What level are the courses targeted at?+
Courses range from beginner (fundamentals & Python for ML) to advanced (MLOps, production LLM features). Mentorship is tailored to the individual's level and goals.
Can I get corporate/onsite workshops?+
Yes — I design customised corporate workshops with pre-work, labs and post-workshop deliverables. Contact for pricing and logistics.
How do you handle intellectual property for projects?+
Project IP is agreed per engagement. For workshops and mentorship, learners typically retain project ownership; for paid consulting, IP terms are agreed in the contract.
How long until I get a reply?+
Typical response time is 48–72 hours via email. For urgent matters, use the contact email indicated on the page.

Contact

Discuss AI projects, workshops or mentoring
Or email: pramod@pramodbarkade.com
You'll receive a reply within 48–72 hours. For urgent enquiries, email directly.