Vacancy Description
What you ll own
- End‑to‑end MLOps/LLMOps reference architecture: ingestion, validation, feature & embedding pipelines, training & fine‑tuning, evaluation, registry, deployment & monitoring (including RAG and agentic workflows)
- Architect, review and approve CI/CD for ML and LLM systems covering code, data, prompt and model artifact versioning; build and release pipelines in Azure DevOps and GitHub Actions; automated unit, integration, contract testing and promotion/rollback with blue‑green, canary across dev, test and production
- Define and govern AI platform foundations on Azure using IaC (Bicep, Terraform); set up AML workspaces, AKS GPU node pools, private networking, VNet integration, Private Link, identity, Managed Identities, PIM, secrets, Key Vault, encryption and data residency controls
- Review and approve production deployment patterns for model and LLM serving (AKS, KServe, AML online endpoints); oversee containerization, inference optimi...
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