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

📌 Gen Ai Developer Mumbai
🏢 Capgemini
📍 Mumbai