Senior AI Engineer / Data Scientist (Agentic AI)

Experience: 8 Years

Location: Office

Employment Type: Full time / Consultant

Role Overview

We are seeking a highly skilled Senior AI Engineer / Data Scientist with 8 years of experience in building enterprise-scale AI, Machine Learning, Data Science, and Generative AI solutions. The ideal candidate should possess strong expertise in designing and implementing Agentic AI systems, multi-agent architectures, LLM orchestration frameworks, RAG pipelines, and AI-driven automation solutions.

This role requires a mix of Data Science, AI Engineering, MLOps, Cloud Engineering, and Software Development skills to develop next-generation autonomous AI platforms that deliver measurable business outcomes.

Key Responsibilities

Agentic AI & Generative AI

- Design and develop Agentic AI solutions using autonomous and multi-agent frameworks.

- Build AI agents capable of 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 using:

- LangGraph

- LangChain

- AutoGen

- CrewAI

- OpenAI Agent Framework

- Microsoft Copilot Studio

Large Language Models (LLMs)

- Fine-tune and optimize LLMs for enterprise use cases.

- Implement prompt engineering, prompt tuning, and evaluation frameworks.

- Develop RAG (Retrieval Augmented Generation) architectures.

- Build semantic search and knowledge retrieval solutions.

- Integrate vector databases such as:

- Azure AI Search

- Milvus





Data Science & Machine Learning

- 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

- Hugging Face

AI Engineering Responsibilities

- 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.

Cloud & Platform Engineering

Azure (Preferred)

- Azure OpenAI

- Azure AI Search

- Azure Machine Learning

Other Cloud Platforms

- AWS Bedrock

- Amazon SageMaker

- Google Vertex AI

Software Development Skills

Strong hands-on programming expertise in:

- Python (Mandatory)

- SQL

- REST APIs

- GraphQL

Experience with
- FastAPI

- Microservices Architecture

- Event-Driven Architecture

Required Qualifications

Education

- Bachelor's or Master's degree in:

- Computer Science

- Data Science





- Artificial Intelligence

- Machine Learning

- Engineering

- Related Discipline

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.

Required Technical Skills

Must Have

✅ Agentic AI Frameworks

✅ Generative AI & LLMs

✅ RAG Architecture

✅ Vector Databases

✅ Python Development

✅ Machine Learning & Data Science

✅ Azure AI Services

✅ MLOps & CI/CD

✅ REST APIs

✅ Cloud Architecture

Good to Have

✅ Semantic Kernel

✅ Microsoft Fabric

✅ Databricks

✅ Knowledge Graphs

✅ GraphRAG

✅ Multi-Agent Systems

✅ AI Governance Frameworks

✅ Copilot Studio

Preferred Certifications

- 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)

Success Metrics

- Successful deployment of enterprise AI agents.

- Reduction in manual effort through AI automation.

- Increased model accuracy and business adoption.

- AI platform scalability, performance, and governance compliance.

- Delivery of measurable business value from Agentic AI initiatives.

Target Titles

- Senior AI Engineer

- Lead AI Engineer

- Staff AI Engineer

- Principal AI Engineer

- Senior Data Scientist (Agentic AI)

- AI Solutions Architect

📌 Senior AI Engineer / Data Scientist (Agentic AI) (Chennai)
🏢 SRM Technologies
📍 Chennai