Python + Gen AI Developer

Capgemini; Hyderabad, Pune District, Bengaluru; Hybrid; INR 1,800,000 - 3,400,000; Full time

Job summary

Capgemini seeks a Senior Backend & Cloud Engineer with strong Python, AWS Cloud, and Generative AI expertise to design and build scalable AI-powered applications. The role involves RAG pipelines, Agentic AI, vector databases, and cloud-native architectures on AWS.

The candidate should have 6+ years of software development experience and 3+ years in GenAI, delivering enterprise-grade solutions and robust REST APIs in a hybrid work setup across India.

Qualifications

• Minimum 6+ years of software development experience.
• Minimum 3+ years of hands-on Generative AI experience.
• Strong Python development expertise.
• Experience deploying AI/ML apps in AWS environments.
• Understanding of distributed systems, cloud-native architectures, and scalable backend development.

Responsibilities

• Design and develop enterprise-grade Generative AI applications using LLMs and AWS services.
• Build and optimize RAG (Retrieval Augmented Generation) pipelines.
• Develop Agentic AI solutions and multi-agent workflows.
• Integrate and manage Vector Databases for semantic search and knowledge retrieval.
• Build scalable REST APIs and microservices using Python frameworks.
• Design event-driven and serverless architectures on AWS.
• Collaborate with product, engineering, and AI teams to deliver innovative AI solutions.
• Ensure application reliability, security, scalability, and performance.

Skills

Python development

Cloud computing

Generative AI

LLM integration

RAG pipelines

Agentic AI

LangChain

Vector databases

REST APIs

Asynchronous programming

Distributed systems

Tools

AWS Bedrock

AWS Lambda

DynamoDB

S3

ECS/EKS

Kubernetes

Terraform

Job description

Senior Python AWS GenAI Engineer | Backend & Cloud Development

Experience

6-12 Years

Location

Hyderabad, Pune, Bangalore, Chennai / Hybrid

Job Overview

We are seeking a highly skilled Senior Backend & Cloud Engineer with strong expertise in Python, AWS Cloud, and Generative AI technologies. The ideal candidate should have hands‑on experience designing and building scalable AI‑powered applications using RAG architectures, Agentic AI frameworks, Vector Databases, and AWS Bedrock. The role involves developing cloud‑native solutions, integrating LLMs, and building high‑performance backend systems on AWS.

Mandatory Requirements

• Minimum 6+ years of overall software development experience
• Minimum 3+ years of hands‑on Generative AI experience
• Strong expertise in Python development
• Experience developing and deploying AI/ML applications in AWS environments
• Strong understanding of distributed systems, cloud‑native architectures, and scalable backend development

Key Responsibilities

• Design and develop enterprise‑grade Generative AI applications using LLMs and AWS services.
• Build and optimize RAG (Retrieval Augmented Generation) pipelines.
• Develop Agentic AI solutions and multi‑agent workflows.
• Integrate and manage Vector Databases for semantic search and knowledge retrieval.
• Build scalable REST APIs and microservices using Python frameworks.
• Design event‑driven and serverless architectures on AWS.
• Collaborate with product, engineering, and AI teams to deliver innovative AI solutions.
• Ensure application reliability, security, scalability, and performance.

Required Technical Skills

Generative AI

• Generative AI / LLM Application Development
• RAG (Retrieval Augmented Generation)
• Agentic AI / AI Agents
• Prompt Engineering
• LangChain / LangGraph
• AWS Bedrock
• MCP/NCP Protocols
• Vector Databases (Pinecone, Weaviate, FAISS, ChromaDB, OpenSearch Vector, etc.)

Python Development

• Core Python
• Multithreading & Multiprocessing
• FastAPI
• Flask
• Django
• REST API Development
• Asynchronous Programming

AWS Cloud

• AWS Bedrock
• AWS Lambda
• DynamoDB
• S3
• SNS
• SQS
• SES
• AWS Step Functions
• AWS Fargate
• API Gateway
• ECS/EKS

DevOps & Cloud Infrastructure

• Docker
• Kubernetes
• Terraform
• CloudFormation
• AWS CDK
• CI/CD Pipelines
• GitHub Actions
• Azure DevOps
• AWS CodePipeline

Monitoring & Observability

• CloudWatch
• Grafana
• Prometheus

Preferred Qualifications

• Experience building production‑grade GenAI applications.
• Knowledge of LLM fine‑tuning and model evaluation.
• Experience with enterprise AI adoption and deployment.
• Exposure to MLOps and AI governance frameworks.
• Strong system design and architecture skills.

What We Are Looking For

• Hands‑on developer, not just a coordinator or architect.
• Strong GenAI implementation experience with real‑world projects.
• Ability to work across AI, Backend, and Cloud technologies.
• Excellent problem‑solving and debugging skills.Strong communication and stakeholder management skills.