Senior AI Platform Engineer

What you'll do

• Build, operate, and improve infrastructure for AI platform services, including MCP servers, model gateways, and control-plane components.
• Own reliability and operational support, including monitoring, incident response, runbooks, and paid on-call.
• Automate platform lifecycle tasks and implement secure runtime patterns for identity, secrets, isolation, and network controls.

What they ask for

• Familiarity with AI platform concepts such as model routing, MCP servers, agentic workflows, RAG systems, or LLM observability.
• Strong experience operating production infrastructure or platform services in Linux environments, using Kubernetes, containers, cloud or private-cloud platforms, infrastructure-as-code, and CI/CD/GitOps tooling.
• Strong automation and scripting skills, for example Terraform, Go, Python, or similar.
• Experience with incident and problem management, demand forecasting, production readiness, and production-platform security fundamentals.

Nice to have

• Experience with internal developer or AI platforms, model gateways, MCP infrastructure, or shared engineering platforms.
• Experience with service mesh, policy-as-code, workload identity, sandboxing, secure runtime environments, multi-tenant designs, regulated environments, or Open AI tools, products and APIs.

Pay

$161,500-$218,500 per year (base salary)

Tools

Linux, Kubernetes, Terraform, Go, Python, MCP servers, model gateway services, GitOps

AI focus

Build and operate the runtime platform for centrally hosted AI services, including MCP server infrastructure, model gateways, and control-plane components; support safe, reliable, observable, and cost-aware AI use across engineering teams.