Agentic AI Engineer for Fabric Lakehouse & Semantic Tech

Tata Consultancy Services; Atlanta (GA); On-site; USD 110,000 - 130,000; Full time

Benefits offered by this job

Discretionary incentive

Medical coverage

Parental leaves

Insurance options

Commuter benefits

Training reimbursement

401K plan

Performance bonus

Student loan refinancing

Job summary

Tata Consultancy Services is seeking a senior AI engineer to design and implement enterprise-grade agentic AI solutions, integrating with Microsoft Fabric Lakehouse/Warehouse and semantic models, for scalable data products.

You will build RAG pipelines using embeddings and vector search, develop ontology-driven data schemas, implement guardrails and cost controls, and collaborate with APIs, cloud security teams, and enterprise applications.

Qualifications

• Agentic AI capabilities including tool calling and multi-agent orchestration.
• Experience with LangChain or equivalent frameworks.
• Proficient in Python and SQL with data engineering skills.

Responsibilities

• Design and implement enterprise-grade agentic AI solutions.
• Integrate AI agents with Microsoft Fabric Lakehouse/Warehouse and APIs.
• Build and optimize RAG pipelines with embeddings and vector search.
• Design ontology-driven semantic models covering entities, relationships, metadata, governance.
• Develop Fabric data pipelines using Data Factory, Notebooks, Spark, SQL, Delta Lake.
• Implement guardrails, access control, logging, and cost optimization.

Skills

Agentic AI

Frameworks

LLM / GenAI

Microsoft Fabric

Ontology / Semantic Modeling

Engineering

Functional

Tools

Python

SQL

Spark/PySpark

REST APIs

CI/CD

Git

Monitoring

Cloud Security

Job description

Tata Consultancy Services is seeking a senior AI engineer to design and implement enterprise-grade agentic AI solutions, integrating with Microsoft Fabric Lakehouse/Warehouse and semantic models, for scalable data products.

You will build RAG pipelines using embeddings and vector search, develop ontology-driven data schemas, implement guardrails and cost controls, and collaborate with APIs, cloud security teams, and enterprise applications.