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Cloud, Edge & AI Platform Engineer

Milwaukee, WI · Onsite · C2C

About the role

Role: Cloud, Edge & AI Platform Engineer

Location: Greater Milwaukee, WI.

locals Preferred.

Exp: 10+yrs

Visa: H4-EAD, GC AND USC.

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.

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