Key skills
AzureKubernetesPythonTerraformAIMLLLMRAGMLOpsMLflowKubeflowAKSCI/CD
About this role
Role Overview
- Build and operate the AI platform infrastructure enabling developers to ship LLM-based services faster
- Implement and maintain Kubernetes-based runtime environments (incl. AKS) for AI workloads
- Manage infrastructure as code with Terraform (modules, environments, CI/CD automation)
- Support LLM workflows: RAG, agents, prompt experimentation, evaluations, and deployment patterns
- Integrate and operate tooling such as Azure AI Foundry, LiteLLM, Langfuse, MLflow
- Orchestrate pipelines using Kubeflow Pipelines and/or Argo Workflows (build, deploy, evaluate)
- Improve platform reliability and observability (monitoring, logging, tracing, cost/perf signals)
- Collaborate closely with developers to streamline DX (APIs, templates, docs, golden paths, automation)
Requirements
- Strong hands-on experience with Kubernetes in production (preferably AKS)
- Solid Terraform expertise (IaC best practices, multi-env setups)
- Practical experience supporting ML/LLM workloads in a platform or DevOps/MLOps context
- Proficiency in Python for automation, scripting, and supporting APIs/evaluation tooling
- Understanding of CI/CD, release processes, and production-grade operations
- Ability to work under tight timelines and deliver pragmatically
Tech Stack
- Azure
- Kubernetes
- Python
- Terraform
Benefits
- Relocation support available