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