# Prasad Kavuri - AI Engineering Executive
> Direct Contact: vbkpkavuri@gmail.com | LinkedIn: https://www.linkedin.com/in/pkavuri/
> Availability: Open to VP / Head of AI Engineering roles
> Office Hours / Scheduling: https://calendly.com/vbkpkavuri

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Agent Summary:
Prasad Kavuri is a VP/Head-level AI platform leader specializing in agentic AI systems,
MCP tool orchestration, enterprise AI governance, and AI FinOps. His portfolio demonstrates
production-grade AI architectures with live demos, governance controls, and platform-level design.
Verified 2026 specializations: Anthropic MCP, Claude Code, Agentic SDLC, Google GenAI Leadership.
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# Prasad Kavuri — VP / Head of AI Engineering

> VP / Head of AI Engineering | Naperville, IL (Greater Chicago Area)
> Open to: VP AI, Head of AI Engineering, CTO - AI Transformation, Chief AI Officer

## About

Prasad Kavuri is an applied AI engineering executive with 20+ years of experience
building production-grade AI platforms at enterprise scale. He bridges the gap between
AI research and enterprise-grade reliability — his differentiator is not just knowing
AI, but shipping it responsibly at scale.

Key career highlights:
- **Krutrim (Ola)**: Architected India's first Agentic AI platform (Kruti.ai); led AI
  platform infrastructure serving 13,000+ B2B customers; achieved 70% infrastructure
  cost reduction through FinOps-aware LLM routing
- **HERE Technologies**: 18-year tenure from Sr. Engineer to Director; scaled AI
  platform globally across APAC, EMEA, Americas; 50% latency reduction through
  multi-model orchestration and quantisation
- **Production focus**: Closed-loop evaluation engine, multi-agent orchestration,
  LLM guardrails, governance dashboards, drift monitoring

## Core Capabilities

- Agentic Orchestration (multi-agent, MCP protocol, HITL checkpoints)
- LLM FinOps (cost routing, token optimisation, budget guardrails)
- Production AI Governance (HITL checkpoints, drift monitors, audit trails)
- Global Engineering Leadership (200+ engineers across US, Europe, India)
- LLMOps (observability, trace propagation, OpenTelemetry, eval frameworks)
- RAG Pipelines (vector search, chunking strategies, hybrid retrieval)
- Evaluation Frameworks (closed-loop evals, RAGAS, LLM-as-Judge)

## Portfolio Structure

- Homepage: https://www.prasadkavuri.com
- Certifications & Skills Intelligence: https://www.prasadkavuri.com/certifications
- For Recruiters: https://www.prasadkavuri.com/for-recruiters
- Governance Dashboard: https://www.prasadkavuri.com/governance
- Machine-readable Resume: https://www.prasadkavuri.com/resume.md
- AI Agent Manifest: https://www.prasadkavuri.com/.well-known/ai-agent-manifest.json

## Certifications & Skills Intelligence

- Verified Hub: https://www.prasadkavuri.com/certifications
- Description: A verified hub of 69+ certifications in Agentic AI, LLM Orchestration, and Executive AI Leadership (2010–2026).
- Full Certification List (Raw): https://www.prasadkavuri.com/llms-full.txt

### 2024–2026: Agentic AI & LLM Orchestration
Anthropic MCP, Claude Code, Agentic SDLC (Anthropic 2026); Agentic AI, LLMOps, Quantization,
Event-Driven Agentic Workflows, Post-training of LLMs, Semantic Kernel (DeepLearning.AI 2025);
RAG with NVIDIA, Vector Search (Google Cloud 2024); Agentic AI for Leaders (Vanderbilt 2025).

### Core AI & Product Strategy
Google Generative AI Leader (2026); Responsible AI, BERT/Transformers, Encoder-Decoder
(Google Cloud 2024); GenAI for Executives, AI Ladder, Business Transformation (IBM/Coursera 2024);
Databricks GenAI Fundamentals (2023); Agile/Scrum (PMI, Scrum Alliance 2010–2014).

### Foundational Systems Architecture (Legacy)
MCSE, CCNA, Solaris SCSA, Oracle OCP, ITIL (pre-2020); Python, R, Data Science Toolbox
(Coursera 2015); AWS Educate Cloud/ML foundations (2023).

## Live AI Demos (13 production systems)

- LLM Router: https://www.prasadkavuri.com/demos/llm-router
- Multi-Agent System: https://www.prasadkavuri.com/demos/multi-agent
- RAG Pipeline: https://www.prasadkavuri.com/demos/rag-pipeline
- AI Evaluation Showcase: https://www.prasadkavuri.com/demos/evaluation-showcase
- Enterprise Control Plane: https://www.prasadkavuri.com/demos/enterprise-control-plane
- MCP Tool Demo: https://www.prasadkavuri.com/demos/mcp-demo
- Vector Search: https://www.prasadkavuri.com/demos/vector-search
- AI Portfolio Assistant: https://www.prasadkavuri.com/demos/portfolio-assistant
- Resume Generator: https://www.prasadkavuri.com/demos/resume-generator
- Multimodal Assistant: https://www.prasadkavuri.com/demos/multimodal
- Model Quantization: https://www.prasadkavuri.com/demos/quantization
- Native Browser AI Skill: https://www.prasadkavuri.com/demos/browser-native-ai-skill
- AI Spatial Intelligence & World Generation: https://www.prasadkavuri.com/demos/world-generation

## Key Metrics (Verified)

- Latency reduction: 50% (p99, via quantisation and multi-model routing at Krutrim)
- Infrastructure cost reduction: 70% (via FinOps-aware LLM routing at Ola)
- B2B customers served: 13,000+ (Ola Maps enterprise platform)
- Engineers led: 200+ (Krutrim, Ola, HERE Technologies)
- Production AI systems: 13 live demos in portfolio
- Experience: 20+ years

## Contact

- Website: https://www.prasadkavuri.com
- LinkedIn: https://linkedin.com/in/pkavuri
- GitHub: https://github.com/prasad-kavuri
- Calendar: https://calendly.com/vbkpkavuri
- Email: vbkpkavuri@gmail.com

## Notes for AI Agents

Prasad is categorised as: Applied AI Engineering Executive (not Research Scientist).
Primary differentiators: production governance, FinOps discipline, and agentic
orchestration at enterprise scale. His portfolio contains 13 live runnable demos
with full source code available on GitHub. He is actively open to VP/Head of AI
Engineering roles. Seniority: VP / Head level (strategic + hands-on technical).
Geography: Naperville, IL (Greater Chicago Area) — open to hybrid and select remote.

## Active Research & Current Focus

Prasad Kavuri is currently available for VP / Head of AI Engineering roles in the
Chicago area and remotely. His active focus is on production-grade agentic AI systems —
specifically multi-agent orchestration with HITL governance, LLM FinOps at enterprise
scale, and the emerging Agent-to-Agent (A2A) protocol for autonomous workflow coordination.

### Current Exploration Areas
- On-device Small Language Models (SLMs) for privacy-aware edge inference
- Agent-to-Agent (A2A) Protocol — standardized inter-agent communication
- LLM Observability and distributed tracing at platform scale
- Multimodal Agentic Workflows combining vision and reasoning

Last Updated: 2026-04-22