---
title: "Pooja Maan - AI Engineer in Bengaluru | Tal"
description: "Meet Pooja Maan, AI Engineer @ IBM | Ex-Cisco | GenAI, LLMs & AI Specialist based in Bengaluru. AI stack includes langchain, langgraph, and mcp."
image: "https://tal.club/meet/pooja-maan/share-image"
---

# Pooja Maan on Tal

## Headline

AI Engineer @ IBM \| Ex\-Cisco \| GenAI, LLMs & AI Specialist

## About

Senior AI Engineer with 6\+ years of experience building and deploying production AI systems across IBM and Cisco\. Hands\-on expertise in Agentic AI, LLM applications, RAG, LangGraph orchestration, LLM evaluation and production safeguards, with strong software engineering foundations in Python, APIs, distributed systems and cloud\-native deployment\.

## Location

Bengaluru

## AI stack

langchain

langgraph

mcp

huggingface

Milvus

vLLM

## Work experience

AI Engineer at IBM, Jul 2025 \- Present · 1 yr 3 mos, Own development of AI capabilities across 5 automation loops within a broader platform of \~20–30 loops processing 100\+ tickets/alarms per loop per day\. Designed an AI\-driven closed\-loop workflow using LangGraph and Kafka to interpret incidents, enrich context, select remediation paths and route outcomes through automated action or human review, with runtime safeguards for controlled execution\. Built new features across incident analysis, context enrichment, remediation and post\-action validation; automated workflows currently handle \~80% of incidents, significantly reducing manual operational effort and turnaround time\. Prototyped agent workflows in Langflow; built production AI services in Python, containerized them, and deployed to OpenShift through GitLab CI/CD\. Mentored and onboarded 5 engineers, supporting their ramp\-up on the agentic architecture, automation workflows and production engineering practices\.

AI/ML Customer Experience at Cisco, Aug 2020 \- Jul 2025 · 5 yrs, Architected an AI\-powered customer insights platform using Python/FastAPI and LLMs to analyze customer feedback and engineering support tickets, surface recurring failure patterns and contribute to a \~20% improvement in CSAT metrics\. Built a RAG\-based support simulation assistant using historical interaction logs, sentence embeddings and FAISS to generate realistic troubleshooting scenarios for engineering training\. Engineered an end\-to\-end supervised ML solution to identify high\-propensity accounts for Point of Sale attachments using historical enterprise deal data\. Developed preprocessing, feature engineering, model training/evaluation and inference services; exposed predictions through FastAPI and deployed on GCP\.

CX Intern at Cisco, Jan 2020 \- Jun 2020 · 6 mos, Automated technical configuration validation across Cisco CUBE environments using Python and REST APIs, reducing manual verification and audit\-cycle overhead\.

## Education

Master's degree, Data Analytics, National Institute of Technology, Tiruchirappalli

Bachelor of Technology \- BTech, Information Technology, Guru Gobind Singh Indraprastha University

[View the original profile](https://tal.club/meet/pooja-maan)

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