AWS Gen AI Engineer

Tata Consultancy Services; Hyderabad, Chennai District, Bengaluru; On-site; INR 1,800,000 - 3,600,000; Full time

Job summary

Tata Consultancy Services in Hyderabad, India seeks an experienced AWS GenAI Engineer to design, build, and scale Generative AI solutions on AWS. You will work across LLMs, RAG pipelines, AI agents, and MLOps, delivering enterprise-grade copilots and intelligent assistants.

Key tasks include designing GenAI solutions on AWS, building RAG pipelines, integrating LLMs with enterprise systems, and ensuring data privacy and security in AI workloads. Strong Python and cloud-native skills are essential.

Qualifications

• Experience designing GenAI/LLM-based solutions on AWS.
• Design and implement RAG pipelines with embeddings and retrieval strategies.
• Strong Python development skills and API integration experience.
• Knowledge of security, governance, and data privacy in AI workloads.
• Experience in deploying and operating AI models in production using MLOps/LMLops.

Responsibilities

• Design and develop Generative AI solutions on AWS with managed/open-source LLMs.
• Build RAG pipelines using enterprise data sources.
• Develop AI agents and copilots for business, engineering, and operations.
• Integrate LLMs with applications and APIs.
• Implement prompt engineering, fine-tuning, and model optimization.
• Operationalize GenAI solutions with MLOps/LLMOps best practices.
• Ensure security and data privacy in AI implementations.
• Collaborate with architects, data engineers, and stakeholders to translate use cases into scalable solutions.
• Support POCs, pilots, and industrialization of GenAI capabilities.
• Deliver GenAI use cases from POC to production.

Skills

LLMs

Prompt engineering

RAG pipelines

Python

AWS SageMaker

AWS Bedrock

LangChain

Vector databases

API integration

Serverless

Education

Bachelors or Masters in Computer Science / AI

4–10+ years software / cloud engineering experience

2+ years GenAI / LLM experience preferred

Tools

S3

DynamoDB

Aurora / RDS

Lambda

ECS / EKS

KMS

VPC

CloudWatch

OpenSearch

Pinecone

FAISS

Chroma

Terraform

Job description

Job Description:

We are looking for an AWS GenAI Engineer to design, build, and scale Generative AI and Agentic AI solutions on AWS. The role involves working across LLMs, RAG pipelines, AI agents, MLOps, and cloud-native architectures, enabling enterprise-grade AI use cases such as copilots, intelligent assistants, document intelligence, and AI-powered automation.

Key Responsibilities

• Design and develop Generative AI solutions on AWS using managed and open-source LLMs
• Build RAG (Retrieval Augmented Generation) pipelines using enterprise data sources
• Develop AI agents and copilots for business, engineering, and operations use cases
• Integrate LLMs with applications, APIs, and enterprise systems
• Implement prompt engineering, fine-tuning, and model optimization strategies
• Operationalize GenAI solutions using MLOps / LLMOps best practices
• Ensure security, compliance, and data privacy in AI implementations
• Collaborate with architects, data engineers, and business stakeholders to translate use cases into scalable solutions
• Support POCs, pilots, and industrialization of GenAI capabilities
• Successfully delivered GenAI use cases from POC to production

Core Technical Skills

Generative AI & LLMs

• Hands-on experience with LLMs (e.g., Amazon Bedrock models, OpenAI-compatible models, open-source LLMs)
• Prompt engineering, prompt chaining, and context optimization
• RAG architecture design (embeddings, vector stores, retrieval strategies)
• Knowledge of fine-tuning vs prompt tuning vs adapters
• Amazon Bedrock (model selection, guardrails, orchestration)
• AWS SageMaker (training, inference, pipelines)
• AWS Lambda, ECS/EKS, Step Functions
• S3, DynamoDB, Aurora / RDS
• IAM, KMS, VPC, CloudWatch for secure AI workloads
• Experience with serverless and container-based AI architectures
• Strong proficiency in Python
• Familiarity with LangChain / LlamaIndex / Semantic Kernel
• REST APIs, FastAPI, Flask
• Experience integrating LLMs with web and enterprise applications
• Embeddings and semantic search
• Vector databases such as OpenSearch, Pinecone, FAISS, Chroma
• Data preprocessing, chunking, and metadata strategies

Nice-to-Have Skills

• Agentic AI frameworks and multi-agent orchestration
• Integration with RPA / workflow engines
• Knowledge of DevOps & IaC (Terraform / CloudFormation)
• Experience in manufacturing, enterprise IT, or large-scale transformation programs
• Exposure to Copilot-style application development
• CI/CD for AI models and prompts
• Model versioning, monitoring, observability
• Experiment tracking and evaluation
• Cost optimization for inference workloads

Education & Experience

• Bachelors or Master’s degree in Computer Science, AI, Data Science, or related fields
• 4–10+ years of software / cloud engineering experience
• 2+ years hands-on experience in GenAI / LLM-based solutions preferred