Summary
✨ AI‑Generated
An engineering role focused on designing and operating secure AI platforms in the cloud. The position covers generative AI integration, containerized services, data workflows, automation, and production-grade infrastructure.
Highlights
Build secure and scalable AI platforms using modern cloud technologies while working on enterprise-grade solutions in regulated environments.
Description
AWS Data & AI Platform Engineer
Charlotte, NC (Hybrid – 3 days/week in client office)
Job Description:
Design, build, and operate secure, scalable AI platforms on AWS for enterprise and regulated financial services environments.
Day-to-Day Responsibilities:
Design, build, and operate secure, scalable AI platforms on AWS for enterprise and regulated environmentsDevelop and manage generative AI solutions using Amazon Bedrock for model integration and deploymentBuild and operate containerized AI services on Amazon EKS supporting Python-based inference and orchestration workloadsDevelop serverless AI workflows using AWS Lambda, API Gateway, and event-driven architecturesImplement secure networking and access controls using VPC, IAM, and private endpointsIntegrate data services (S3, DynamoDB, messaging/streaming platforms) to enable AI pipelines and RAG architecturesEstablish CI/CD, monitoring, logging, and operational controls aligned to enterprise/regulatory standardsCollaborate with security, architecture, and risk teams to ensure compliance with financial services requirements
Basic Qualifications:
5+ years building cloud platforms on AWS2+ years hands-on with Amazon Bedrock, EKS/Kubernetes, AWS Lambda, and core AWS networking services8+ years Python development supporting APIs, AI services, or automation workflows5+ years designing secure, highly available, scalable distributed systems5+ years working in regulated environments (financial services, banking, or insurance)
Nice to Have:
Experience supporting AI/ML or generative AI platforms in productionKnowledge of data security, model governance, auditability, and access controlsExperience with Infrastructure as Code (Terraform, CloudFormation, or CDK)Exposure to CI/CD pipelines and production operations in enterprise environments
