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Ind & Func AI Decision Science Analyst

S&C; Global Network

Gurugram

2-5 years

Today

$20.5K–32.5K/yr

Full time

Onsite

Skills Required

LLM

RAG

Gen AI

Agentic AI Systems

Azure OpenAI

Prompt Engineering

LLM Fine-tuning

LangChain

LlamaIndex

Vector Database

Model Context Protocol (MCP)

Multi-Agent Systems

AI Agent Orchestration

Python

SQL

Description

S&C; Global Network is hiring an AI Decision Science Analyst focused on Agentic AI and Intelligent Automation. The role involves designing and delivering enterprise-scale AI solutions using LLMs, multi-agent systems, and cloud AI platforms.

Company: S&C; Global Network

Role: Ind & Func AI Decision Science Analyst – Agentic AI & Intelligent Automation

Location: Gurugram

Experience

- 2-5 years of experience
- Minimum 2 years of experience in AI/ML
- Demonstrated expertise in Generative AI, LLMs, Agentic AI systems, and Multi-Agent Systems
- Experience in enterprise AI application development
- Experience building and deploying production-grade AI solutions in a consulting or enterprise environment preferred

Qualification

- Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Information Technology, Data Science, Mathematics, Statistics, or related disciplines
- Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Information Technology, Data Science, Mathematics, Statistics, or related disciplines
- BE
- BTech
- MTech
- MS
- MBA
- Excellent academic record

Responsibilities

- Design, develop, fine-tune, evaluate, and deploy enterprise-scale AI solutions
- Build intelligent AI agents that reason, plan, collaborate, and autonomously execute complex business workflows
- Develop reusable agent orchestration frameworks, AI accelerators, and enterprise AI components
- Design and implement MCP servers and integrations for AI agents and enterprise applications
- Design Human-in-the-Loop workflows requiring business approvals or validations
- Build AI copilots, autonomous agents, and workflow automation solutions
- Build, fine-tune, evaluate, and optimize LLMs for enterprise use cases
- Develop Generative AI applications using prompt engineering, structured outputs, function calling, and tool calling




- Evaluate AI models for accuracy, latency, grounding quality, safety, hallucination rates, and business KPIs
- Optimize prompts, agent workflows, and reasoning strategies
- Implement model evaluation pipelines and continuous improvement mechanisms
- Design and implement enterprise RAG solutions
- Develop document ingestion, chunking, metadata enrichment, indexing, and retrieval pipelines
- Optimize grounding strategies and retrieval quality
- Build scalable enterprise knowledge management solutions
- Integrate AI agents with ServiceNow, Microsoft Graph API, Microsoft Teams, Splunk, Azure Functions, Azure SQL, and REST APIs
- Build secure MCP integrations for enterprise systems
- Develop scalable enterprise automation workflows leveraging AI agent orchestration
- Design resilient API integrations with security, authentication, logging, retries, and error handling
- Implement AI guardrails, Responsible AI principles, governance controls, and compliance standards
- Design evaluation frameworks for AI quality, grounding, latency, hallucination rates, and business outcomes
- Build observability dashboards for agent execution, token consumption, workflow performance, cost, and operational health
- Ensure enterprise AI applications meet security, governance, and compliance requirements
- Collaborate with architects, product owners, and engineering teams to deliver scalable cloud-native AI solutions
- Deploy AI applications using Azure AI Foundry, Azure OpenAI, Azure Functions, and enterprise cloud platforms
- Participate in architecture, design, code reviews, testing, deployment, and production support
- Implement CI/CD pipelines and MLOps practices for AI solution lifecycle management
- Stay updated with advancements in Generative AI, Agentic AI, MCP, LLMs, and enterprise AI technologies
- Develop reusable frameworks, accelerators, templates, and best practices




- Create technical documentation and mentor junior team members

Nice To Have

- Experience with LangChain
- Experience with LlamaIndex
- Experience with AutoGen
- Experience with CrewAI
- Experience with Semantic Kernel
- Experience with Azure AI Search
- Experience with Azure Functions
- Experience with Microsoft Graph API
- Experience with ServiceNow Integration
- Experience with Splunk
- Experience with Microsoft Teams Integration
- Experience with Vector Databases
- Experience with Docker
- Experience with Kubernetes
- Experience with Azure DevOps
- Experience with CI/CD
- Experience with MLOps
- Experience with AI Guardrails
- Experience with Responsible AI
- Experience with AI Evaluation Frameworks
- Experience with Observability & Monitoring
- Experience with Git
- Experience with cloud platforms such as Azure, AWS, or GCP

More Skills Large Language Models (LLMs), LangGraph, AI Refinery, Azure AI Foundry, Retrieval-Augmented Generation (RAG), Function Calling, Tool Calling, REST APIs, AI Model Evaluation, Enterprise AI Solution Development, AutoGen, CrewAI, Semantic Kernel, Azure AI Search, Azure Functions, Microsoft Graph API, ServiceNow Integration, Splunk, Microsoft Teams Integration, Docker, Kubernetes, Azure DevOps, CI/CD, MLOps, AI Guardrails, Responsible AI, AI Evaluation Frameworks, Observability & Monitoring, Git, Azure, AWS, GCP

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