Azure DevOps Engineer
Robotics Technologies LLC
Bonita Springs, FL, United States
3 days ago
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Role details
Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source
Tech stack
Artificial Intelligence
Application Performance Management
Microsoft Azure
Bash Shell
Cloud Computing
Cloud Computing Security
Continuous Integration
DevOps
Github
Subnetting
Python (Programming Language)
Log Analysis
+20 more
Windows PowerShell
Role-Based Access Control
Prometheus
Azure Machine Learning
YAML
Cloud Monitoring
Delivery Pipeline
Grafana
AI Platforms
Kubernetes
Information Technology
Bicep
Azure AKS
Data Management
Machine Learning Operations
Terraform
Api Management
Docker
Key Vault
Databricks
Job description
- Azure: AKS, Functions, Storage, Key Vault, Monitor/Log Analytics, API Management, Event Hub/Service Bus.
- DevOps: Azure DevOps, GitHub, ACR, Helm, Docker; Terraform or Bicep/ARM.
- Security/Governance: Azure Policy, RBAC, Managed Identity, Key Vault, Defender for Cloud.
- Observability: Application Insights, Azure Monitor, Grafana/Prometheus.
- Languages: YAML, PowerShell, Python; optional Bash. Equal Opportunity Employer
Requirements
- 5+ years in DevOps/SRE, with 3+ years on Azure.
- Hands on with Azure DevOps (Repos, Pipelines, Artifacts), GitHub Actions, and YAML based CI/CD.
- Strong IaC skills (Terraform or Bicep/ARM); experience managing AKS and container registries (ACR).
- Proficiency with PowerShell and/or Python for automation; familiarity with Docker and Helm.
- Experience operating Azure Machine Learning (workspaces, endpoints, registries) and integrating ML workflows in CI/CD.
- Solid understanding of cloud security (RBAC, Key Vault, Managed Identity, policies), networking (VNet, subnets, Private Link), and cost management, * Strong experience with Azure DevOps, AKS, and Azure Machine Learning.
- Proficiency in CI/CD, IaC, and container orchestration.
- Familiarity with cloud security best practices and compliance frameworks.
- Knowledge of AI/ML deployment workflows and traditional IT infrastructure., * Experience with GPU workloads on AKS or AML; model serving (Azure ML Managed Online Endpoints, Kubernetes Inference).
- Familiarity with Databricks, Fabric, or other data platforms that feed AI services.
- Certifications: Azure DevOps Engineer Expert, Azure Solutions Architect, or equivalent.
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Prepare application
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