Home/Jobs/Senior AI Engineer / Data Scientist (Agentic AI) Senior AI Engineer / Data Scientist (Agentic AI) SRM Technologies Chennai 8+ years Today $53.0K–66.3K/yr Full-time Onsite Skills Required LLM RAG Agentic AI Gen AI LangChain OpenAI Agent Framework Hugging Face Azure OpenAI GraphRAG Machine Learning Data Science LangGraph AutoGen CrewAI Microsoft Copilot Studio Description Senior AI Engineer / Data Scientist role focused on Agentic AI, generative AI, and enterprise-scale AI platforms. The position combines data science, AI engineering, MLOps, cloud engineering, and software development.

Role: Senior AI Engineer / Data Scientist (Agentic AI) Location: Chennai, Tamil Nadu, India | Office Experience 8+ years of experience

8+ years in Data Science, Machine Learning, AI Engineering, or Software Engineering

3+ years of hands-on experience with Generative AI and LLMs

2+ years of hands-on experience implementing Agentic AI solutions

Experience delivering enterprise-scale AI platforms Qualification Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, or related discipline

Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, or related discipline

Microsoft Certified: Azure AI Engineer Associate

Microsoft Certified: Azure Data Scientist Associate

Databricks Certified Data Engineer

AWS Machine Learning Specialty

Generative AI Certifications (Microsoft/OpenAI) Responsibilities Design and develop Agentic AI solutions using autonomous and multi-agent frameworks

Build AI agents with reasoning, planning, tool usage, memory management, and workflow orchestration

Implement multi-agent systems for enterprise workflows, analytics, customer service, and decision intelligence

Develop AI copilots, virtual assistants, and autonomous business agents

Design AI orchestration architectures with LangGraph, LangChain, AutoGen, CrewAI,



OpenAI Agent Framework, and Microsoft Copilot Studio

Fine-tune and optimize LLMs for enterprise use cases

Implement prompt engineering, prompt tuning, and evaluation frameworks

Develop RAG architectures

Build semantic search and knowledge retrieval solutions

Integrate vector databases such as Azure AI Search and Milvus

Develop predictive and prescriptive analytics models

Build recommendation systems and forecasting solutions

Apply advanced statistical analysis and machine learning techniques

Design feature engineering pipelines and model optimization strategies

Build and deploy models using Scikit-Learn, XGBoost, TensorFlow, PyTorch, and Hugging Face

Develop scalable AI services and APIs

Build enterprise-grade AI microservices

Create reusable AI accelerators and frameworks

Design AI governance and observability frameworks

Implement AI monitoring and model performance tracking

Develop AI safety, guardrails, and responsible AI controls Additional Responsibilities Use Azure OpenAI, Azure AI Search, and Azure Machine Learning on Azure as preferred cloud platform

Work with AWS Bedrock, Amazon SageMaker, and Google Vertex AI as other cloud platforms

Use Python, SQL, REST APIs, and GraphQL in hands-on development

Work with FastAPI, Microservices Architecture, and Event-Driven Architecture

Deliver measurable business outcomes from autonomous AI platforms

Meet success metrics around enterprise AI agent deployment, reduced manual effort, improved accuracy and adoption, scalability, performance, and governance compliance Nice To Have Semantic Kernel





Microsoft Fabric

Databricks

Knowledge Graphs

GraphRAG

Multi-Agent Systems

AI Governance Frameworks

Copilot Studio More Skills Vector Databases, Python, Azure AI Services, MLOps, CI/CD, REST APIs, Cloud Architecture, Azure AI Search, Azure Machine Learning, AWS Bedrock, Amazon SageMaker, Google Vertex AI, SQL, GraphQL, FastAPI, Microservices Architecture, Event-Driven Architecture, Scikit-Learn, XGBoost, TensorFlow, PyTorch, Prompt Engineering, Prompt Tuning, Evaluation Frameworks, Semantic Search, Knowledge Retrieval, Predictive Analytics, Prescriptive Analytics, Recommendation Systems, Forecasting, Statistical Analysis, Feature Engineering, Model Optimization, AI Governance, Observability, AI Monitoring, Model Performance Tracking, AI Safety, Guardrails, Responsible AI Controls Other Full time / Consultant employment type

Industry: Technology

Target titles include Senior AI Engineer, Lead AI Engineer, Staff AI Engineer, Principal AI Engineer, Senior Data Scientist (Agentic AI), and AI Solutions Architect Follow for Daily AI Tutorials Prepare for this role Recommended resources to build the skills for this position. Sponsored. Generative AI with Large Language Models Coursera Comprehensive LLM course covering transformer architecture, fine-tuning, RLHF, and deployment.

Deep Learning Specialization Coursera

Five-course deep learning series covering CNNs, RNNs, transformers, and ML strategy. Functions, Tools and Agents with LangChain Coursera Advanced LangChain covering function calling, tool use, and conversational agents. More LLM jobs AI Engineer Prescient Healthcare Group Gurugram Today Principal Machine Learning Engineer Equinix Bengaluru Today AI Cloud Engineer Solventum Bengaluru Today Engineer, Machine Learning Tools Qualcomm Hyderabad Today AI Engineer NTT Ltd Bengaluru Today AI/ML Engineer Optum Hyderabad Today

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