3+ years in platform, DevOps, SRE, or cloud engineering
Hands-on experience with Kubernetes, including deployments and troubleshooting
Experience with infrastructure as code (Terraform) and GitOps tooling
Solid experience with at least one major cloud provider (Azure or AWS)
Experience with observability tools like OpenTelemetry, Prometheus, and Grafana
Scripting skills in Python, Go, or Bash, with CI/CD experience
Responsibilities
Operate and evolve a Kubernetes-based platform for AI workloads
Integrate and manage access to cloud-hosted foundation models
Deliver infrastructure as code and GitOps workflows
Build monitoring, alerting, and tracing for AI workloads
Help design and prototype self-hosted model serving
Harden the platform with security measures
Support internal product teams through documentation and troubleshooting
Benefits
Opportunity to work with cutting-edge AI technologies
Collaborative environment with internal product teams
Focus on evolving and improving platform capabilities
Exposure to multi-cloud environments and advanced observability tools
Potential for professional growth in a rapidly evolving field
Full Job Description
What you will do
Operate and evolve a Kubernetes-based platform for AI workloads, including LLM gateways, agent and tool-integration gateways, and agent runtimes
Integrate and manage access to cloud-hosted foundation models across multiple providers, covering routing, quotas, fallbacks, cost controls, and tenant isolation
Deliver infrastructure as code and GitOps workflows
Build monitoring, alerting, and tracing for AI workloads
Help design and prototype self-hosted model serving, including GPU workloads and inference runtimes
Harden the platform with secrets management, network policies, authentication and authorization, and audit logging
Support internal product teams through documentation, onboarding, and troubleshooting
What you will need
3+ years in platform, DevOps, SRE, or cloud engineering
Hands-on experience with Kubernetes, including deployments, networking, and troubleshooting
Experience with infrastructure as code (Terraform) and GitOps tooling (Argo CD, Flux, or similar)
Solid experience with at least one major cloud, Azure or AWS
Experience with observability tools such as OpenTelemetry, Prometheus, and Grafana
Scripting and coding skills in Python, Go, or Bash, and CI/CD experience
Nice to have
Experience with LLM gateways or proxies, or LLM observability and tracing tools
Familiarity with managed model services from major cloud providers, such as Azure or AWS
Understanding of agent frameworks and tool-integration protocols such as Model Context Protocol (MCP)
Experience running GPU workloads or model inference serving
Experience in multi-tenant, regulated, or compliance-driven environments
