AWS AI Engineer

Responsibilities

• Design, develop, and deploy Agentic and Generative AI solutions using AWS services such as Amazon Bedrock and SageMaker
• Integrate foundation models and LLMs into applications using custom model endpoints or Bedrock
• Build and manage AI pipelines for inference, prompt orchestration, fine-tuning, and evaluation
• Architect cloud-native solutions using AWS core services including Lambda, ECS/EKS, API Gateway, and DynamoDB
• Implement Infrastructure as Code (IaC) using CloudFormation, CDK, or Terraform
• Design and maintain CI/CD pipelines and enforce AWS security best practices (IAM, KMS, VPC)
• Implement monitoring, logging, and alerting using CloudWatch and X-Ray to ensure production readiness

Requirements

• 5+ years of experience in full-stack development (front-end and back-end)
• Hands-on expertise with AWS cloud-native architectures and services
• Practical experience building or integrating Agentic or Generative AI solutions
• Proficiency in Python or a similar backend language
• Experience with REST APIs, microservices, and asynchronous processing
• Familiarity with containerization (Docker) and orchestration (ECS/EKS)
• Experience with Infrastructure as Code (Terraform, CDK, or CloudFormation)
• Proven ability to build production-grade systems and translate business problems into technical AI solutions

Benefits

• Paid time off including vacation, company holidays, personal days, and sick leave
• Medical, dental, and vision coverage
• Retirement savings plans (e.g., 401(k))
• Life and disability insurance
• Employee assistance programs

About the Company

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world. With a team of 340,000 members in more than 50 countries, Capgemini leverages market-leading capabilities in AI, cloud, and data to deliver end-to-end services and solutions.