AI-ML Engineer

Tata Consultancy Services; Hyderabad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Tata Consultancy Services in Hyderabad is seeking talented AI engineers to design, develop, and deploy enterprise-scale Generative AI applications using large language models. You will build AI-powered assistants, copilots, and document intelligence systems, enabling scalable workflow automation.

You will work with Retrieval Augmented Generation (RAG), vector databases, and multi-agent architectures, implementing ingestion, embeddings, and semantic retrieval.

Responsibilities

• Design, develop, and deploy enterprise-scale Generative AI applications using LLMs.
• Develop AI-powered assistants, copilots, document intelligence systems, and workflow automation solutions.
• Build production-ready GenAI applications leveraging AWS Bedrock and foundation models.
• Implement model orchestration frameworks for complex reasoning and task execution.
• Design AI systems capable of handling structured and unstructured enterprise data.
• Design and implement intelligent Multi-Agent Systems using LangGraph, LangChain, CrewAI, or similar frameworks.
• Develop autonomous AI agents capable of task planning, execution, reasoning, and collaboration.
• Build agent orchestration frameworks for business process automation.
• Retrieval Augmented Generation (RAG) solutions for knowledge discovery and conversational search.
• Build document ingestion, chunking, embedding generation, and semantic retrieval pipelines.
• Develop vector search applications using ChromaDB, FAISS, Pinecone, OpenSearch, or equivalent vector databases.
• Build scalable data ingestion pipelines for structured, semi-structured, and unstructured data sources.
• Develop ETL workflows using Python and PySpark for large-scale document processing.
• Process PDFs, Word documents, emails, websites, and enterprise knowledge repositories.
• Implement document parsing, metadata extraction, data cleansing, normalization, and enrichment.
• Create embedding generation and indexing frameworks.

Job description

• Design, develop, and deploy enterprise-scale Generative AI applications using Large Language Models (LLMs).
• Develop AI-powered assistants, copilots, document intelligence systems, and workflow automation solutions.
• Build production-ready GenAI applications leveraging AWS Bedrock and foundation models.
• Implement model orchestration frameworks for complex reasoning and task execution.

Design AI systems capable of handling structured and unstructured enterprise data.

• Design and implement intelligent Multi-Agent Systems using LangGraph, LangChain, CrewAI, or similar frameworks.


• Develop autonomous AI agents capable of task planning, execution, reasoning, and collaboration.


• Build agent orchestration frameworks for business process automation.

Retrieval Augmented Generation (RAG)

• Architect and develop enterprise RAG solutions for knowledge discovery and conversational search.


• Build document ingestion, chunking, embedding generation, and semantic retrieval pipelines.


• Develop vector search applications using ChromaDB, FAISS, Pinecone, OpenSearch, or equivalent vector databases.


• Build scalable data ingestion pipelines for structured, semi-structured, and unstructured data sources.


• Develop ETL workflows using Python and PySpark for large-scale document processing.


• Process PDFs, Word documents, emails, websites, and enterprise knowledge repositories.


• Implement document parsing, metadata extraction, data cleansing, normalization, and enrichment.


• Create embedding generation and indexing frameworks.