Gen AI Developer

TymblHub; Mumbai; On-site; INR 690,000 - 970,000; Full time

Job summary

Capgemini in Mumbai is seeking a GenAI Developer with 6–11 years of experience to design and build AI agents using AWS Bedrock and orchestration frameworks. The role involves creating RAG solutions with vector databases and knowledge bases, and building ingestion pipelines for parsing, OCR, embeddings, and indexing.

You will implement Bedrock Guardrails, IaC with AWS CDK, and work to optimize prompts, model performance, latency, and costs while collaborating with product and architecture teams.

Qualifications

• Develop AI agents using AWS Bedrock and agent orchestration frameworks.

Responsibilities

• Develop AI agents using Bedrock and orchestration frameworks.
• Design and implement Retrieval-Augmented Generation (RAG) solutions with vector databases and knowledge bases.
• Build and integrate custom tools, APIs, MCP connectors, and external services for AI agents.
• Develop document ingestion pipelines including parsing, OCR, chunking, embeddings, and indexing workflows.
• Integrate AWS Bedrock Guardrails and content safety controls into applications.
• Implement Infrastructure as Code using AWS CDK and JSON-based configurations.
• Optimize prompts, model performance, latency, and operational costs.
• Collaborate with product, architecture, and support teams for AI solution delivery.
• Monitor application logs, usage metrics, and performance through CloudWatch.

Skills

GenAI

LLM concepts

Prompt Engineering

RAG Architecture

Vector Databases

Embeddings

Model Evaluation

Tools

AWS Bedrock

AWS Lambda

AWS Step Functions

DynamoDB

S3

API Gateway

CloudWatch

IAM

Secrets Manager

AWS CDK

Job description

# Gen AI DeveloperCapgeminiPosted on October 19, 2026---Experience6 - 11 yrsSalary (CTC)₹6.9L - ₹9.7LJob LocationMumbai, IndiaVacancy5DesignationArtificial Intelligence DeveloperJob TypeNot specified---## Job Description**Role & responsibilities**\\*\\*Key Responsibilities\\*\\*- Develop AI Agents using AWS Bedrock and agent orchestration frameworks such as LangGraph, CrewAI, or similar.- Design and implement Retrieval-Augmented Generation (RAG) solutions using vector databases (OpenSearch, LanceDB) and knowledge bases.- Build and integrate custom tools, APIs, MCP connectors, and external services for AI agents.- Develop document ingestion pipelines including parsing, OCR, chunking, embeddings, and indexing workflows.- Integrate AWS Bedrock Guardrails and content safety controls into applications.- Implement Infrastructure as Code using AWS CDK and JSON-based configurations.- Optimize prompts, model performance, latency, and operational costs.- Collaborate with product, architecture, and support teams for AI solution delivery.- Monitor application logs, usage metrics, and performance through CloudWatch.Required Skills\\*\\*GenAI\\*\\*- LLM concepts, Prompt Engineering- RAG Architecture- Agentic AI- Vector Databases- Embeddings and Semantic Search- Model Evaluation and Guardrails\\*\\*AWS\\*\\*- Bedrock- Lambda- Step Functions- DynamoDB- S3- API Gateway- CloudWatch- IAM- Secrets Manager- AWS CDK\\*\\*Development\\*\\*- Python (Mandatory)- REST APIs- Git/GitHub- JSON/YAML- CI/CD pipelines---