---
title: "Prateek Verma - Deputy Manager (Senior Consultant) in Bengaluru | Tal"
description: "Meet Prateek Verma, AI Platform Architect | MLOps & LLMOps | Production GenAI & Agentic Systems | AWS/Azure/GCP | 35% Cost Optimization based in Bengaluru. AI stack includes hugging face, langchain, and langgraph."
image: "https://tal.club/meet/prateek-verma-1/share-image"
---

# Prateek Verma on Tal

## Headline

AI Platform Architect \| MLOps & LLMOps \| Production GenAI & Agentic Systems \| AWS/Azure/GCP \| 35% Cost Optimization

## About

🧠 AI Platform Architect \| MLOps & LLMOps \| Production GenAI & Agentic Systems I design and operate production AI platforms\. Over 7\+ years, I’ve worked across enterprise environments \(Deloitte, Capgemini, Philips, Hitachi, Unilever\), focusing on one thing: taking AI systems from experimentation to reliable, scalable production platforms\. My work sits at the intersection of MLOps, LLMOps, and AI platform architecture — owning systems end\-to\-end: from orchestration design to deployment, governance, and continuous optimization\. What I own in production AI platform architecture — multi\-agent systems, orchestration layers, MCP integrations, and human\-in\-the\-loop workflows RAG systems — retrieval design, grounding strategies, evaluation \(RAGAS\), and continuous quality improvement Model lifecycle governance — experiment tracking, versioning, deployment strategies, retraining, and drift monitoring Inference cost engineering — token optimization, context compression, and cost\-aware architecture \(35% cost reduction delivered\) AI platform CI/CD — automated pipelines, release governance, and environment\-aware deployments Production impact ⚡ 40% faster deployment cycles through pipeline architecture decisions 💰 35% reduction in inference cost through token and payload optimization 🧠 Continuous LLM quality improvement via structured evaluation pipelines 🔍 Full observability across ML \+ LLM systems \(monitoring, drift, feedback loops\) Platforms I work across MLOps: MLflow · Airflow · SageMaker · Kubeflow · Feast · Evidently AI LLMOps: LangChain · LangGraph · RAG pipelines · evaluation frameworks Cloud: AWS · Azure · GCP Infra: Kubernetes · Docker · Terraform I focus on production systems, not prototypes — where reliability, cost, governance, and scale matter as much as model performance\. 🤝 Open to conversations around AI platforms, MLOps, LLMOps, agentic systems, and production GenAI architecture

## Location

Bengaluru

## AI stack

hugging face

langchain

langgraph

ollama

## Work experience

Deputy Manager \(Senior Consultant\) at Deloitte, Jul 2025 \- Present · 11 mos, Bengaluru

Professional I \(Associate Consultant\) at Capgemini, Jan 2022 \- Jun 2025 · 3 yrs 6 mos, Pune, Maharashtra, India

Associate at Firstsource, May 2020 \- Nov 2021 · 1 yr 7 mos, Bengaluru, Karnataka, India

Process Analyst at FUGO Services, Mar 2019 \- May 2020 · 1 yr 3 mos, Bengaluru, Karnataka, India

Associate at Innovsource, Oct 2018 \- Mar 2019 · 6 mos, Bengaluru, Karnataka, India

[View the original profile](https://tal.club/meet/prateek-verma-1)

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