MLOps Manager — Role Mandate

Mandate: Design and operationalize the enterprise Azure + Databricks MLOps operating model, with centrally governed production deployment and controlled market access to non-production settings.
Define the end-to-end deployment operating model across sandbox, development, test/UAT, and production.
Create production access policies, separation-of-duties rules, approval gates, and exception processes.
Establish the central MLOps team as the owner of production model deployment and release management.
Design reusable deployment patterns for batch, real-time, and GenAI workloads on Azure + Databricks.
Define MLflow and Unity Catalog standards for model registration, versioning, promotion, and lineage.




Implement enterprise monitoring standards for model performance, drift, reliability, alerts, and rollback.
Own FinOps governance, including tagging, usage attribution, Databricks compute policies, budgets, alerts, and showback/chargeback.
Define security patterns using Entra ID, RBAC, managed identities, Key Vault, private networking, and audit logging.
Create measurable SLAs for model onboarding, deployment, incident response, and production support.
Lead stakeholder alignment across market DS teams, central DS, engineering, security, platform, and finance.

📌 Mlops Manager Bengaluru (India)
🏢 Nityo Infotech
📍 India