AI Engineering · Platform Leadership

Anil
Prasad

Building production AI systems that work
when stakes are real.

Head of Engineering & Product with 20+ years delivering AI/ML platforms across Fortune 100 companies. From ISRO neural networks to agentic AI systems governing billions in capital decisions today.

View My Work → Connect on LinkedIn
0+ Years in AI/ML
$0B+ Business Outcomes
0 Open-Source Platforms
0+ Engineers Led
Anil Prasad — Head of Engineering and Product
100 Most Influential AI Leaders · USA 2024
Anil Prasad Head of Engineering & Product
About

Where Deep
Experience Meets
What's Next

I started my AI career at ISRO, training neural networks before transformers existed. What has stayed constant across three decades is a belief that AI systems are only as valuable as their reliability in production — not their performance on a benchmark.

Across Tech, Techstartups, Healthcare, Lifesciences, Energy & Utilities, Insurance, Banking, and Fintech I have led platform transformations that generated over $4B in measurable business outcomes. The work I am most proud of is not the technology — it is the trust that business stakeholders placed in AI systems I built, because those systems told the truth about uncertainty when it mattered.

I co-founded the CAIO Circle Tri-State Chapter to build the executive AI leadership community that I wished had existed when I was navigating these decisions alone. I publish and speak to share what the journey actually looks like from inside enterprise AI — not the demo, the production.

Stanford University
IEEE Member
CAIO Circle Co-Founder
100 Most Influential AI Leaders · 2024
IISc Research Background
Forbes Technology Council (Aspirant)
▸
2024 – Present
Head of Engineering & Product
Duke Energy Corporation · CASPAR Platform
▸
2024 – 2024
Head of Software, Products, Data & AI Engineering
Ambry Genetics · Genomics Platform
▸
2021 – 2024
VP Engineering · AI Platforms
R1 RCM · CloudmedAI Integration ($4.1B acquisition)
▸
2011 – 2018
Director - Software Engineering
UnitedHealth Group · Enterprise Data, AI and Analytics Platform
▸
2000 – 2024
Software, Data and AI Engineering Roles · Software, Data, AI/ML Platforms
Xcel Energy . Medtronic · Accenture . Wipro . ISRO/IISC
Platforms

Production AI,
at Scale

Three open-source platforms built from real production requirements. No demos. No prototypes.

⚡
CASPAR
Cost Intelligence Platform

Renewable energy interconnection cost forecasting platform at Duke Energy. Combines cost modeling, Variance narrative generation, and automated workflow orchestration for capital program decision support.

LLM RAG Time-Series ML FERC Compliance Cost Forecasting
$2.3B+
Portfolio Governed
<8%
MAPE Target
95%+
Groundedness
🔬
PulseFlow
MLOps Platform · Open Source

Enterprise MLOps framework for production model lifecycle management. Covers experiment tracking, model registry, automated evaluation pipelines, drift detection, and governance dashboards built for regulated industries.

MLOps Model Registry Drift Detection CI/CD ML Governance
Opensrc
License
G-ARVIS
Eval Framework
Autoeval
CI Integration
👁
SAM3
Perception Hub · Enterprise AI

Enterprise AI perception platform combining computer vision, NLP, and multimodal document understanding. Powers intelligent document processing, anomaly detection, and real-time data extraction at scale across unstructured enterprise data.

Computer Vision NLP Multimodal Document AI Real-time
Multimodal
Architecture
Real-time
Inference
Entgrade
Scale
Framework

The G-ARVIS
Framework

Six dimensions of production LLM health — distilled from building AI systems that govern billions in capital decisions across regulated industries.

Read the Full Article →
G
Groundedness
Output traceability to source. Hallucination prevention.
A
Accuracy
MAPE + ECE. Calibrated confidence, not just correctness.
R
Reliability
P99 latency and SLO adherence under real load.
V
Variance
Semantic stability across identical inputs.
I
Inference Cost
Cost per correct answer, not per API call.
S
Safety
Guardrail calibration and compliance audit trail.
Expertise

Full-Stack
AI Leadership

From data infrastructure to model deployment to business translation — the complete stack of skills required to ship AI that actually works in production.

🤖
AI / ML / Deep Learning
LLM Fine-tuningRAG SystemsAgentic AINLPComputer VisionTime-SeriesForecasting
⚙️
MLOps & LLMOps
Model LifecycleDrift DetectionEvaluation PipelinesFeature StoresCI/CD MLObservability
🗄️
Data Engineering
Data WarehousingBig DataSparkdbtLakehouseStreamingETL/ELT
📊
Analytics & BI
Executive DashboardsTableauPower BIFinancial AnalyticsKPI Design
☁️
Cloud & Platform
AWSAzureGCPKubernetesMicroservicesAPIsSaaS Architecture
🏛️
AI Governance
SOX ComplianceHIPAAExplainabilityBias AuditRisk FrameworksSafety
Writing

Thought Leadership
From the Trenches

All Articles →
Medium Feb 2026 18 min
The LLM Metrics That Actually Matter in Production

Why benchmark scores are a distraction — and the 8 measurements that will make or break your AI system when real money is on the line. Introduces the G-ARVIS framework for production LLM observability.

LLMOps GenAI Production AI G-ARVIS
LinkedIn Feb 2026 5 min
Why Agentic AI Changes the Evaluation Problem Entirely

Single-turn accuracy metrics break down when your LLM is taking multi-step actions. What needs to change in your observability stack before you ship agentic workflows to production.

Agentic AILLMOps
LinkedIn Jan 2026 4 min
The $4.1B Acquisition Lesson Nobody Talks About

What the CloudmedAI integration at R1 RCM taught me about AI platform architecture, technical due diligence, and the engineering decisions that make or break an acquisition thesis.

Platform EngineeringM&A
Medium Dec 2025 12 min
RAG Is Not a Search Problem. It's a Reliability Problem.

Most RAG failures I have diagnosed in production have nothing to do with the retrieval algorithm. They are groundedness failures, chunking failures, and context window management failures in disguise.

RAGLLMProduction
Recognition

Earned in
Production

🏆
100 Most Influential AI Leaders
USA · 2024
⚡
IEEE Member
Institute of Electrical & Electronics Engineers
🎓
Stanford University
Alumnus
🌐
CAIO Circle Co-Founder
Tri-State Chapter
Organizations where this expertise creates impact
Google Meta Nvidia Anthropic OpenAI Uber Intuit Amazon Netflix Microsoft
Contact

Let's Build
Something
That Matters

Open to conversations about engineering leadership, AI platform architecture, speaking engagements, and advisory roles at companies building AI that has to work when stakes are real.

LinkedIn Medium GitHub
Open to roles in AI Engineering Leadership · Platform Architecture · Advisory · DM on LinkedIn
Anil.Prasad
HEAD OF ENGINEERING & PRODUCT · AI PLATFORM LEADER
LINKEDIN MEDIUM #humanwritten