Cloud, Edge & AI Platform Engineer

Role: Cloud, Edge & AI Platform Engineer
Location: Greater Milwaukee, WI.
locals Preferred.
Exp: 10+yrs 
Day one onsite 

Role Summary: 
Design and deliver secure, cloud-native AI platforms that connect medical imaging devices and hospital edge environments to cloud-hosted LLM services. Own the end-to-end solution across edge Kubernetes gateways, AWS infrastructure, APIs, identity, security, observability, and CI/CD.

Key Responsibilities: 
- Build hardened k3s, Helm, and NGINX edge gateways for secure device-to-cloud communication.
- Design and automate AWS platforms using Terraform, including ECS/Fargate, ALB, CloudFront, WAF, IAM, ACM, ElastiCache/Valkey, API Gateway, Lambda, and DynamoDB.
- Develop and integrate AI/LLM services using Amazon Bedrock, model routing, prompt orchestration, semantic caching, RAG, and agentic workflows.
- Implement secure authentication and authorization using OAuth 2.0, OIDC, PKCE, JWT, GEHC STO Cloud IDAM token exchange.
- Troubleshoot hybrid edge-to-cloud networking, DNS, TLS/SNI, ingress, caching, API, and production reliability issues.
- Establish CI/CD, automated testing, observability, performance engineering, and DevSecOps practices.
- Produce architecture documentation and collaborate with engineering, security, network, product, and clinical platform teams.
- Performance and load Testing.

Core Skills
AWS • Amazon Bedrock • Generative AI/LLMs • Kubernetes/k3s • Helm • NGINX • Terraform • Docker • ECS/Fargate • CloudFront • WAF • API Gateway • OAuth/OIDC/JWT   • Node.js/TypeScript • Go • Java • Python • GitLab CI/CD • OpenAPI • Grafana • k6.

 Preferred Experience: 
Experience delivering secure, scalable platforms in healthcare or other regulated environments, including clinical network segmentation, container hardening, TLS lifecycle management, distributed tracing, and hybrid edge/cloud architecture.