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ENGINEERING

Cloud Infrastructure Engineer, AI Workloads

Design the cloud foundations enterprise AI runs on: GPU clusters, inference gateways, private model endpoints and the network and identity plumbing that lets regulated clients use frontier models safely.

  • Dallas
  • Engineering
  • Full-time

What you’ll do

  • Architect client landing zones where AI workloads meet enterprise security and residency requirements
  • Automate provisioning of model gateways, vector databases and eval infrastructure
  • Optimise inference cost and performance across providers and regions
  • Ensure compliance controls are enforced in code, not slide decks
  • Partner with client platform teams through build, handover and their first quarter of operations

What we’re looking for

  • 4+ years with AWS, Azure or GCP, including their AI stacks (Bedrock, Azure OpenAI Service, Vertex AI)
  • Strong Terraform or CloudFormation, with multi-account/landing-zone experience
  • Experience with GPU capacity planning, spot strategies and inference autoscaling
  • Understanding of private networking for model endpoints: PrivateLink, VPC peering, egress control
  • Knowledge of FinOps practices for AI spend — token budgets, showback, anomaly alerts

What we offer

  • Competitive salary
  • Comprehensive benefits package
  • Remote work options
  • Cloud certification budget
  • Flexible work arrangements
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