Senior AI DevOps / MLOps Engineer

Role overview

Responsibilities

• check_circle Design and maintain CI/CD and MLOps pipelines for AI/ML solutions.
• check_circle Deploy and operate AI workloads on Azure Machine Learning, Azure OpenAI, AKS, Azure Functions, and Azure DevOps.
• check_circle Automate infrastructure using Terraform, Bicep, or ARM templates.
• check_circle Implement secure deployment practices: RBAC, Key Vault, managed identities, private endpoints, network isolation.
• check_circle Set up monitoring, logging, alerting, and operational support for AI services and model endpoints.
• check_circle Support model versioning, release management, rollback, and production governance.
• check_circle Work closely with data scientists, AI engineers, cloud architects, security, and banking IT teams.
• check_circle Ensure solutions meet banking standards for security, auditability, resilience, and compliance.

Basic qualifications

• 7+ years of DevOps, Cloud Engineering, Platform Engineering, or related experience.
• Strong experience with Azure DevOps, CI/CD pipelines, Git, YAML, and release management.
• Experience with Azure Machine Learning and/or MLOps platforms.
• Practical knowledge of Azure OpenAI, GenAI applications, or AI service deployment.
• Experience with Docker, Kubernetes, and AKS.
• Experience with Infrastructure as Code: Terraform, Bicep, or ARM.
• Good understanding of monitoring tools such as Azure Monitor, Application Insights, Log Analytics, Grafana.
• Scripting skills in PowerShell, Python, or Bash.
• Experience working in regulated enterprise environments, preferably banking, fintech, or insurance.

Preferred qualifications

• Nice to have: Experience with RAG pipelines, prompt orchestration, MLflow, or Prompt Flow.
• Knowledge of Microsoft data platforms: Databricks, Synapse, Data Factory, Microsoft Fabric, Purview.
• Understanding of AI governance, model risk, data privacy, and audit requirements.
• Experience with Microsoft security tools such as Defender for Cloud or Sentinel.