Jobs · Engineering

AI Platform Engineer (LLMOps)

Workerbee · United States · 2 mo ago
RemoteRemoteEngineeringContract

C2C not available | No third-party suppliers

About Workerbee

Workerbee connects workers with employers through trusted introductions. By joining Workerbee you can be matched for project-based, contract, or permanent opportunities with leading organizations. Over time, Workerbee helps you:

  • Keep a living record of what you have actually accomplished
  • See how your experience carries across roles and paths
  • Explore options without pressure to apply
  • Move through change with clarity instead of urgency

About the role

In this work, you help employers solve complex problems and bring real value through hands-on expertise in AI platform engineering, model operations, and cloud infrastructure.

Responsibilities

  • Stand up and operate the infrastructure that AI applications run on, including model serving, inference routing, and orchestration layers
  • Build CI/CD, infrastructure as code, and environment automation with tools such as Terraform, Kubernetes, Docker, and GitHub Actions
  • Instrument evaluation, tracing, cost tracking, and guardrails so teams can measure model quality and spend in production
  • Harden the platform for security and compliance, covering secrets management, identity, data residency, and access control
  • Partner with application and data teams to remove deployment friction and shorten the path from experiment to production

Requirements

  • 5+ years in platform, DevOps, or infrastructure engineering, with recent work supporting AI or ML workloads
  • Depth in at least one major cloud plus Kubernetes, Terraform, and container-based deployment
  • Practical experience with LLM serving, GPU capacity planning, or inference cost optimization
  • Working knowledge of observability and evaluation tooling for non-deterministic systems
  • Ability to operate independently, document decisions, and advise clients on tradeoffs

Benefits

  • Earlier visibility into opportunities
  • Better-fit introductions
  • Access to meaningful work
  • Less application noise
  • A network that improves over time

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