Generative AI Engineer - AWS Bedrock & SageMaker

Tata Consultancy Services; Malvern (Chester County); On-site; USD 120,000 - 140,000; Full time

Benefits offered by this job

Discretionary Annual Incentive

Comprehensive Medical Coverage

Parental Leaves

Insurance Options

Certification & Training Reimbursement

Vacation & Holidays

401K Plan

Performance Bonus

Job summary

Tata Consultancy Services in the United States is seeking an experienced AI/ML Engineer to design, develop, and deploy Generative AI and ML solutions on AWS Bedrock and SageMaker.

The role focuses on building scalable data pipelines, RAG workflows, AI agents, and production-ready models, collaborating with business, data engineering, and cloud teams to optimize performance, governance, and costs.

Qualifications

• Bachelor's degree in Computer Science or related field.
• Experience designing Generative AI on AWS Bedrock/SageMaker.
• Strong Python, PySpark, and SQL skills.
• Hands-on ML/DL, NLP, and prompt engineering expertise.

Responsibilities

• Design, develop, and deploy AI/ML and Generative AI solutions using AWS services such as Bedrock and SageMaker.
• Build and optimize RAG pipelines, LLM-based applications, AI agents, and model inference workflows.
• Develop scalable data pipelines and MLOps frameworks for training, deployment, monitoring, and governance.
• Collaborate with business, data engineering, and cloud teams to deliver production-ready AI solutions while controlling cost.

Skills

Python

PySpark

SQL

Machine Learning

Deep Learning

NLP

Generative AI

LLMs

Prompt Engineering

RAG

AI Agents

REST APIs

Model Deployment & Monitoring

Education

BACHELOR OF COMPUTER SCIENCE

Tools

AWS Bedrock

AWS SageMaker

S3

Lambda

IAM

RDS

CloudWatch

MLOps

MLflow

CI/CD

Docker

Kubernetes

Terraform

LangChain

LangGraph

LlamaIndex

FastAPI

Job description

Tata Consultancy Services in the United States is seeking an experienced AI/ML Engineer to design, develop, and deploy Generative AI and ML solutions on AWS Bedrock and SageMaker.

The role focuses on building scalable data pipelines, RAG workflows, AI agents, and production-ready models, collaborating with business, data engineering, and cloud teams to optimize performance, governance, and costs.