AI Platform Engineer

JOB SUMMARY The AWS Data & AI Platform Engineer will be responsible for designing, building, and operating secure and scalable AI platforms on AWS within enterprise and regulated environments. This role involves developing and managing generative AI solutions, containerized AI services on Amazon EKS, and serverless AI workflows. A key aspect of the position is implementing robust security measures, integrating various data services for AI pipelines, and establishing comprehensive CI/CD, monitoring, logging, and operational controls that align with enterprise and regulatory standards in financial services. Collaboration with security, architecture, and risk teams is essential to ensure compliance with financial services requirements. Key Responsibilities Design, build, and operate secure, scalable AI platforms on AWS for enterprise and regulated environments. Develop and manage generative AI solutions using Amazon Bedrock for model integration and deployment. Build and operate containerized AI services on Amazon EKS supporting Python-based inference and orchestration workloads. Develop serverless AI workflows using AWS Lambda, API Gateway, and event-driven architectures. Implement secure networking and access controls using VPC, IAM, and private endpoints. Integrate data services such as S3, DynamoDB, and messaging/streaming platforms to enable AI pipelines and RAG architectures. Establish CI/CD, monitoring, logging, and operational controls aligned to enterprise and regulatory standards. Collaborate with security, architecture, and risk teams to ensure compliance with financial services requirements. Required Qualifications Minimum 5+ years of experience building cloud platforms on AWS. Minimum 2+ years of hands-on experience with Amazon Bedrock, EKS/Kubernetes, AWS Lambda, and core AWS networking services. Minimum 8+ years of Python development experience supporting APIs, AI services, or automation workflows. Minimum 5+ years of experience designing secure, highly available, and scalable distributed systems. Minimum 5+ years of experience working in regulated environments such as financial services, banking, or insurance. Bachelors degree in Computer Science, Engineering, or equivalent work experience. 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 (Terraform, CloudFormation, or CDK). Exposure to CI/CD pipelines and production operations in enterprise environments. Education: Bachelors Degree