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Ved PrajapatiVP
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Ved Prajapati

@vedprajapati

Cloud & AI Engineer and founder building production multi-agent and RAG systems on scalable cloud-native infrastructure.

United Kingdom
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What I'm looking for

I’m looking for a hands-on role where I can build production-grade Cloud & AI systems—multi-agent workflows and RAG included—on scalable cloud-native infrastructure, with strong engineering ownership, measurable outcomes, and practical product thinking.

I’m a Cloud & AI Engineer and founder of Outclass, an adaptive learning platform focused on practical, modern skill development. I design and build production-grade AI and cloud systems—from multi-agent workflows to RAG pipelines—so they’re reliable, scalable, and usable.

My engineering foundation comes from Harvard CS50x and MIT 6.S191 (Deep Learning), complemented by Stanford CS234 (Reinforcement Learning). I’ve also earned 40+ industry certifications across AWS, Google, Cisco, Intel, Red Hat, Aruba, NetApp, Aviatrix, and ZEDEDA, which keeps my work grounded in real-world platforms and best practices.

I’m comfortable delivering end-to-end systems, combining Python/TypeScript development with cloud architecture, networking, and virtualization. I’ve built solutions like an autonomous multi-agent DevOps automation system (LangGraph + Groq API, AWS Lambda, DynamoDB, EventBridge) and an enterprise RAG system with semantic search (AWS Bedrock embeddings, EKS, FastAPI, React, and monitoring).

At work, I prioritize structured decision-making, clear communication, and practical outcomes. Whether I’m solving distributed systems challenges, tuning performance, or improving security and observability, I aim to turn complex ideas into production-ready products that people can actually benefit from.

Experience

Work history, roles, and key accomplishments

Education

Degrees, certifications, and relevant coursework

SU

Stanford University

Reinforcement Learning (CS234), Reinforcement Learning

2026 -

Grade: Passed

Completed Stanford CS234 Reinforcement Learning covering Markov decision processes, policy gradients, deep Q-networks, and reward-driven optimization.

MT

Massachusetts Institute of Technology

Deep Learning (6.S191), Deep Learning

2026 -

Grade: Passed

Completed MIT 6.S191 Deep Learning covering neural networks, CNNs, RNNs, transformers, and generative models, applied to real-world AI systems and production projects.

Harvard University logoHU

Harvard University

Certificate (CS50x), Computer Science

2025 -

Grade: Certificate with Distinction

Completed CS50x covering programming, data structures, algorithms, memory management, Python, SQL, web development, and cybersecurity, earning a Certificate with Distinction.

WA

Westfield Academy

GCSE, GCSE (Computer Science, Economics, Mathematics)

2021 - 2026

Completed GCSE coursework including programming fundamentals, algorithms, data structures, computational thinking, and analytical problem-solving.

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