Gen AI Developer

Capgemini; Mumbai; Ibrido; INR 1.200.000 - 2.400.000; Tempo pieno

Descrizione del lavoro

Capgemini Mumbai is seeking a GenAI developer to build AI agents using AWS Bedrock, orchestration frameworks, and retrieval-augmented generation workflows. You will implement vector databases, embeddings, and knowledge bases, and design scalable ingestion pipelines.

You will optimize prompts, latency, and costs; craft REST APIs, CI/CD pipelines, and IaC with AWS CDK; monitor logs via CloudWatch and collaborate across product, architecture, and support teams.

Competenze

• Experience with GenAI development on cloud platforms.
• Hands-on experience building AI agents and orchestration workflows.
• Strong understanding of data privacy and safety controls.

Mansioni

• Develop AI agents using AWS Bedrock and orchestration frameworks.
• Design RAG solutions with vector databases and knowledge bases.
• Build tools, APIs, MCP connectors, and external services for AI agents.
• Create document ingestion pipelines with parsing, OCR, chunking, embeddings, and indexing.
• Integrate Bedrock Guardrails and content safety into applications.
• Implement IaC using AWS CDK and JSON configs.
• Optimize prompts, model performance, latency, and costs.
• Collaborate with product, architecture, and support teams.
• Monitor logs and metrics via CloudWatch.

Conoscenze

LLM concepts

Prompt Engineering

RAG Architecture

Agentic AI

Vector Databases

Embeddings & Semantic Search

Model Evaluation & Guardrails

Strumenti

Bedrock

Lambda

Step Functions

DynamoDB

S3

API Gateway

CloudWatch

IAM

Secrets Manager

AWS CDK

Descrizione del lavoro

Role & 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