Job Summary (List Format):
-
DevOps & Automation:
- Design, implement, and maintain Azure DevOps pipelines (YAML) for building, testing, security scanning, and releasing AI/ML models.
- Implement Infrastructure as Code (IaC) using ARM templates, Terraform, or Bicep.
- Manage artifact repositories and ensure container image signing for compliance.
-
Cloud & Platform Management:
- Administer Azure environments, including AKS clusters for containerized workloads and GPU-enabled pools for ML training.
- Standardize and support business applications and Azure Machine Learning workspaces.
-
Security & Compliance:
- Enforce governance guardrails for IT and AI workloads.
- Ensure compliance with regulatory and internal security standards.
-
Collaboration & Support:
- Partner with data science teams to enable rapid ML model deployment.
- Work with IT stakeholders to ensure reliability and scalability of enterprise systems.
-
Technical Skills & Experience:
- 5+ years in DevOps/SRE, with 3+ years on Azure.
- Hands-on experience with Azure DevOps (Repos, Pipelines, Artifacts), GitHub Actions, and YAML-based CI/CD.
- Proficient in IaC (Terraform, Bicep/ARM), AKS, ACR, PowerShell and/or Python, Docker, Helm.
- Experience with Azure Machine Learning (workspaces, endpoints, registries) and ML workflows in CI/CD.
- Strong understanding of cloud security (RBAC, Key Vault, Managed Identity), networking (VNet, subnets, Private Link), and cost management.
-
Preferred Experience:
- Experience with GPU workloads on AKS/AML, model serving (Azure ML Managed Online Endpoints, Kubernetes Inference).
- Familiarity with Databricks, Fabric, or similar data platforms.
- Relevant Azure certifications (DevOps Engineer Expert, Solutions Architect, etc.).
-
Core Tools & Technologies:
- Azure (AKS, Functions, Storage, Key Vault, Monitor/Log Analytics, API Management, Event Hub/Service Bus)
- DevOps (Azure DevOps, GitHub, ACR, Helm, Docker, Terraform/Bicep/ARM)
- Security/Governance (Azure Policy, RBAC, Managed Identity, Defender for Cloud)
- Observability (Application Insights, Azure Monitor, Grafana/Prometheus)
- Languages: YAML, PowerShell, Python (Bash optional)
-
Key Deliverables (First 90 Days):
- Baseline CI/CD templates for AI services and documented promotion strategies.
- Reference AKS/AML environments deployed via IaC with guardrails and runbooks.
- Unified observability stack with dashboards, alerts, and SLOs for pipeline and platform health.
- Playbooks for incident response and change management; backlog of automation opportunities.
-
Soft Skills:
- Strong communication and collaboration with AI developers, security, and operations teams.
- Focus on automation, reliability, documentation, and ability to operate in regulated environments.
or continue with email
-
DevOps & Automation:
- Design, implement, and maintain Azure DevOps pipelines (YAML) for building, testing, security scanning, and releasing AI/ML models.
- Implement Infrastructure as Code (IaC) using ARM templates, Terraform, or Bicep.
- Manage artifact repositories and ensure container image signing for compliance.
-
Cloud & Platform Management:
- Administer Azure environments, including AKS clusters for containerized workloads and GPU-enabled pools for ML training.
- Standardize and support business applications and Azure Machine Learning workspaces.
-
Security & Compliance:
- Enforce governance guardrails for IT and AI workloads.
- Ensure compliance with regulatory and internal security standards.
-
Collaboration & Support:
- Partner with data science teams to enable rapid ML model deployment.
- Work with IT stakeholders to ensure reliability and scalability of enterprise systems.
-
Technical Skills & Experience:
- 5+ years in DevOps/SRE, with 3+ years on Azure.
- Hands-on experience with Azure DevOps (Repos, Pipelines, Artifacts), GitHub Actions, and YAML-based CI/CD.
- Proficient in IaC (Terraform, Bicep/ARM), AKS, ACR, PowerShell and/or Python, Docker, Helm.
- Experience with Azure Machine Learning (workspaces, endpoints, registries) and ML workflows in CI/CD.
- Strong understanding of cloud security (RBAC, Key Vault, Managed Identity), networking (VNet, subnets, Private Link), and cost management.
-
Preferred Experience:
- Experience with GPU workloads on AKS/AML, model serving (Azure ML Managed Online Endpoints, Kubernetes Inference).
- Familiarity with Databricks, Fabric, or similar data platforms.
- Relevant Azure certifications (DevOps Engineer Expert, Solutions Architect, etc.).
-
Core Tools & Technologies:
- Azure (AKS, Functions, Storage, Key Vault, Monitor/Log Analytics, API Management, Event Hub/Service Bus)
- DevOps (Azure DevOps, GitHub, ACR, Helm, Docker, Terraform/Bicep/ARM)
- Security/Governance (Azure Policy, RBAC, Managed Identity, Defender for Cloud)
- Observability (Application Insights, Azure Monitor, Grafana/Prometheus)
- Languages: YAML, PowerShell, Python (Bash optional)
-
Key Deliverables (First 90 Days):
- Baseline CI/CD templates for AI services and documented promotion strategies.
- Reference AKS/AML environments deployed via IaC with guardrails and runbooks.
- Unified observability stack with dashboards, alerts, and SLOs for pipeline and platform health.
- Playbooks for incident response and change management; backlog of automation opportunities.
-
Soft Skills:
- Strong communication and collaboration with AI developers, security, and operations teams.
- Focus on automation, reliability, documentation, and ability to operate in regulated environments.
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