AWS AI/ML Engineer (GenAI, Agents, MCP & RAG)

Tata Consultancy Services; India; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Tata Consultancy Services (TCS) is seeking an experienced AWS AI/ML Engineer with GenAI, LLMs, AI agents, MCP, and RAG expertise to design, develop, and deploy enterprise-scale GenAI solutions on AWS.

The role involves building RAG-based workflows with vector databases, implementing MCP integrations to connect LLMs with business tools, and applying MLOps for production-grade AI applications, collaborating with data engineers and stakeholders.

Qualifications

• Experience designing Generative AI solutions on AWS.
• Hands-on experience building RAG (Retrieval-Augmented Generation) solutions.
• Experience with AI Agents, autonomous workflows, and tool-calling frameworks.
• Knowledge of Model Context Protocol (MCP) and AI-agent integrations.
• Expertise in prompt engineering and LLM evaluation techniques.

Responsibilities

• Design and develop Generative AI applications using AWS AI/ML services.
• Build and deploy RAG-based solutions using vector databases and enterprise data sources.
• Develop AI agents capable of multi-step reasoning, tool usage, and workflow orchestration.
• Implement MCP integrations to connect LLMs with enterprise tools, APIs, and data systems.
• Fine-tune, evaluate, and optimize foundation models for business use cases.
• Design scalable and secure AI architectures on AWS.
• Develop prompt engineering, guardrails, and responsible AI frameworks.
• Implement MLOps and LLMOps practices for model deployment and monitoring.
• Collaborate with data engineers, architects, and business stakeholders to deliver AI-driven solutions.
• Monitor AI application performance, cost, and model quality in production.

Skills

AWS

GenAI

LLMs

RAG

AI Agents

MCP

LangChain

LangGraph

Vector Databases

SageMaker

Python

MLOps

Docker

Kubernetes

Terraform

MLflow

Tools

LangChain

LangGraph

LlamaIndex

FastAPI

REST APIs

Docker

Kubernetes

Terraform

MLflow

Job description

Role & responsibilities

Job Title: AWS AI/ML Engineer (GenAI, Agents, MCP & RAG)

Location: India

Experience: 6+ Years

Employment Type: Full-Time

Preferred candidate profile

Job Summary

We are looking for an experienced AWS AI/ML Engineer with expertise in Generative AI, Large Language Models (LLMs), AI Agents, Model Context Protocol (MCP), and Retrieval-Augmented Generation (RAG). The ideal candidate will design, develop, and deploy enterprise-scale AI solutions on AWS, leveraging foundation models, agentic AI frameworks, vector databases, and MLOps best practices. This role requires strong software engineering skills combined with hands-on experience in building production-grade GenAI applications.

Key Responsibilities

• Design and develop Generative AI applications using AWS AI/ML services.
• Build and deploy RAG-based solutions using vector databases and enterprise data sources.
• Develop AI agents capable of multi-step reasoning, tool usage, and workflow orchestration.
• Implement MCP integrations to connect LLMs with enterprise tools, APIs, and data systems.
• Fine-tune, evaluate, and optimize foundation models for business use cases.
• Design scalable and secure AI architectures on AWS.
• Develop prompt engineering, guardrails, and responsible AI frameworks.
• Implement MLOps and LLMOps practices for model deployment and monitoring.
• Collaborate with data engineers, architects, and business stakeholders to deliver AI-driven solutions.
• Monitor AI application performance, cost, and model quality in production.

Required Skills

AI/ML & Generative AI

• Strong experience with Generative AI and Large Language Models (LLMs).
• Hands-on experience building RAG (Retrieval-Augmented Generation) solutions.
• Experience with AI Agents, autonomous workflows, and tool-calling frameworks.
• Knowledge of Model Context Protocol (MCP) and AI-agent integrations.
• Expertise in prompt engineering and LLM evaluation techniques.
• Experience with embeddings, semantic search, and vector databases.

AWS Services

• Amazon Bedrock
• SageMaker
• Lambda
• API Gateway
• ECS/EKS
• Step Functions
• DynamoDB
• S3
• OpenSearch
• CloudWatch
• IAM

Programming

• Python
• LangChain
• LangGraph
• LlamaIndex
• FastAPI
• REST APIs

Data & Vector Databases

• Pinecone
• Weaviate
• Chroma
• FAISS
• OpenSearch Vector Engine
• PostgreSQL (pgvector)

MLOps / LLMOps

• CI/CD for AI applications
• Model deployment and monitoring
• MLflow
• Docker
• Kubernetes
• GitHub Actions / Jenkins
• Terraform

Preferred Skills

• Experience with OpenAI, Anthropic Claude, Meta Llama, or Mistral models.
• Experience developing enterprise AI copilots and conversational assistants.
• Knowledge of multimodal AI (text, image, audio, video).
• Experience with Responsible AI, AI governance, and security frameworks.
• AWS Certified Machine Learning Engineer or AWS Certified AI Practitioner certification.
• Experience working with healthcare, banking, insurance, or other regulated industries.

Mandatory Skills

• AWS
• Amazon Bedrock
• Python
• Generative AI
• LLMs
• RAG
• AI Agents
• MCP (Model Context Protocol)
• LangChain / LangGraph
• Vector Databases
• SageMaker
• MLOps

Keywords for Sourcing

AWS AI Engineer, GenAI Engineer, Generative AI Engineer, LLM Engineer, AI/ML Engineer, Amazon Bedrock, SageMaker, RAG, Retrieval Augmented Generation, AI Agents, Agentic AI, MCP, Model Context Protocol, LangChain, LangGraph, LlamaIndex, Vector Database, Pinecone, OpenSearch, Python, Prompt Engineering, LLMOps, MLOps, Semantic Search, Embeddings, AI Copilot, Foundation Models

Nice-to-Have Skills

• CrewAI
• AutoGen
• Semantic Kernel
• OpenAI APIs
• Anthropic Claude
• Hugging Face
• Fine-tuning
• Knowledge Graphs
• GraphRAG
• Multi-Agent Systems
• Kubernetes
• Terraform
• Serverless AI Architectures

Experience Range: 6-12+ Years

Target Profiles: GenAI Engineer, LLM Engineer, AI Platform Engineer, AI Solutions Engineer, AI Architect, Applied AI Engineer, Machine Learning Engineer (GenAI Focus).