Enterprise AI Engineer at FactSet | TopGenAIJobs

Enterprise AI Engineer

FactSet

Bengaluru

8-12 years

Today

₹38–63 LPA

Full-time

Onsite

Skills Required

Gen AI

LLM

RAG

Agentic AI Frameworks

Vector Database

Python

AWS

Model Context Protocol (MCP)

A2A

Description

We are looking for an Enterprise AI Engineer with strong hands-on experience in designing and implementing Gen-AI solutions for enterprise use cases.

Role: Enterprise AI Engineer

Location: Bengaluru

Experience:

5+ years of experience in enterprise software development, backend engineering, or systems integration
7+ Years of IT experience
3+ Years of AI/ML
8 to 12 years

Key Skills:

Model Context Protocol (MCP)
Artificial Intelligence
generative ai
A2A
Python
AWS
Enterprise IT - Integrations
Agentic AI Frameworks
RAG
Token Economics
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG) pipelines
vector databases
API development (REST, gRPC)
SAP via web services
enterprise ticketing tools like JIRA/BMC Helix

Qualification:

Graduation or Masters in Computer science & Engineer or related field

Role Focus:

designing and implementing Gen-AI solutions
working with IT application teams to discover, validate, and implement practical Gen-AI use cases
analyzing existing IT processes, SOPs, ticket patterns, knowledge documents, system logs, and operational workflows to identify automation opportunities
designing AI solution architectures using LLMs, RAG pipelines, agentic workflows, APIs, and integration layers
building, testing, deploying, and supporting Gen-AI solutions in enterprise environments
ensuring security, governance, auditability, scalability, and compliance

Nice to have:

Enterprise IT Systems Understanding
AI Delivery in Production
ITSM
Strong Communication Skills

Other:

Department: ENT - SIE GDFT & AI|ML
Open Positions: 1
Posted On: 19-Jun-2026

Prepare for this role

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Python for Everybody Specialization

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Python 3 Programming Specialization

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Intermediate Python covering classes, inheritance, APIs, and data processing.

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Comprehensive LLM course covering transformer architecture, fine-tuning, RLHF, and deployment.