Practice Architect II AI/ML
Tasks
- Architect azure infrastructure environments
- Architect end to end ai solutions with azure services
- Automate manual processes for efficiency
- Create infrastructure as code templates
- Design azure platform and devops solutions
- Develop technical assessments and architecture reviews
- Enforce production change control
- Ensure ai performance security and compliance
- Establish MLOps practices
- Facilitate stakeholder meetings and executive presentations
- Improve monitoring and analytics systems
- Integrate ai models into applications and pipelines
- Lead technical design sessions and mentor teams
- Operate azure devops pipelines and workflows
- Support azure migrate efforts
Perks/Benefits
- 401k
- Employee assistance program
- Health spending account
- Life insurance
- Long-term disability
- Medical/Dental/Vision
- Short-term disability
- Time Off Leave
- Transportation benefits
Skills/Tech-stack
Anomaly Detection | Azure CLI | Azure Container | Azure Container Registry | Azure Data | Azure Data Factory | Azure DevOps | Azure Kubernetes | Azure Kubernetes Service | Azure Machine Learning | Azure OpenAI | Azure Resource | Azure Resource Manager | Azure Resource Manager Templates | Azure Synapse | Azure Synapse Analytics | Bicep | Business Continuity | Cognitive Services | Container Registry | Continuous Delivery | Continuous integration | Data Factory | Databricks | Disaster Recovery | Git | ISO 27001 | ISO NIST | Infrastructure as Code | Kubernetes Service | MLOps | Machine Learning | Microservices | Monitoring | NIST | Powershell | Predictive Modeling | Python | Resource Manager Templates | Synapse Analytics | Terraform | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Solutions | AI Solutions Architect | Architect | Platform | Platform Architect | Solutions Architect
Regions
Countries
States
Cities
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