Job Summary
The AWS Data & AI Platform Engineer will lead the development, configuration, deployment, and maintenance of secure, scalable AI platforms on AWS for regulated financial services environments. This role focuses on enabling Generative AI and advanced analytics use cases while meeting enterprise requirements for security, compliance, reliability, and operational excellence. The engineer will design and operate AI services, build serverless workflows, integrate data services, and establish CI/CD pipelines and operational controls to support production workloads.
Key Responsibilities
• Design, build, and support AI platforms on AWS using Amazon Bedrock for Generative AI and model integration.
• Develop and operate containerized AI services on Amazon EKS, supporting Python-based inference and orchestration workloads.
• Build serverless AI workflows using AWS Lambda, API Gateway, and event-driven architectures.
• Implement secure cloud networking and access controls using VPC, IAM, private endpoints, and service networking.
• Integrate data services, including Amazon S3, DynamoDB, and messaging or streaming services, to support AI pipelines and Retrieval-Augmented Generation (RAG) architectures.
• Establish CI/CD pipelines, monitoring, logging, and operational controls aligned with enterprise and regulatory standards.
• Collaborate with security, architecture, and risk teams to ensure compliance with financial services requirements.
• Support the deployment, maintenance, reliability, and operational excellence of cloud-based AI platforms.
Required Qualifications
• 5+ years of experience building cloud platforms on AWS.
• Hands-on experience with Amazon Bedrock, Amazon EKS/Kubernetes, AWS Lambda, and core AWS networking.
• Strong Python development experience for APIs, AI services, or automation.
• Experience designing secure, highly available, and scalable systems.
• Familiarity with regulated environments, including financial services, banking, insurance, or similar industries.
Preferred Qualifications
• Experience supporting AI/ML or Generative AI platforms in production.
• Knowledge of data security, model governance, auditability, and access controls.
• Experience with Infrastructure as Code tools such as Terraform, AWS CloudFormation, or AWS CDK.
• Exposure to CI/CD pipelines and production operations in enterprise environments.
