| Mandatory Skills | Powershell |
| JD | Key Responsibilities Automation Platform Development (Lite-Touch) Design and build a Lite-Touch Automation Platform that enables scalable workstation provisioning and configuration management. Responsibilities include: - Architect and develop an enterprise automation framework enabling deterministic workstation configuration deployment
- Implement modular automation workflows supporting policy-driven configuration management
- Ensure 100% repeatable configuration outcomes
- Enable input-driven configuration provisioning using structured configuration inputs
- Integrate automation capabilities with enterprise request and service management platforms
- Implement logging traceability and auditability across automation workflows
- Manage configuration artifacts using version-controlled configuration management practices
- Eliminate configuration drift and manual build inconsistencies through automated enforcement
Configuration Quality Verification Platform Design and develop a Configuration Quality Verification Platform that validates workstation configurations against requested standards and enterprise quality policies. Responsibilities include: - Build automated verification workflows validating workstation configuration states
- Implement compliance validation aligned with enterprise quality standards
- Detect configuration drift and unauthorized configuration changes
- Verify alignment between requested and deployed configurations
- Generate automated reports and audit artifacts for regulatory compliance
- Enable engineering teams to perform automated quality assurance for workstation environments
Required Qualifications Professional Experience - 10 years of professional software engineering experience
- 5 years designing automation platforms or infrastructure automation systems
- Proven experience building enterprise automation frameworks or internal developer tools
- Strong DevOps engineering background
Programming - Advanced PowerShell automation and scripting frameworks
- C# / .NET application and platform development
Source Control & Engineering Practices - Git-based development workflows
- Branching strategies and pull request processes
- Code review and engineering quality practices
- Modern DevOps development methodologies
Artificial Intelligence Engineering Experience Hands-on experience integrating AI capabilities into development workflows working with: - Semantic Kernel
- Azure AI Foundry
- Comparable enterprise AI orchestration frameworks
Experience working with modern LLM ecosystems such as: - Anthropic Claude models
- Gemini models
- Microsoft Copilot models
AI Development Practices: - Prompt engineering
- AI-assisted development workflows
- Codex-driven development
- AI agent orchestration
Preferred Qualifications - Distributed systems design
- Automation platform architecture
- Modular framework development
- Event-driven systems
- CI/CD pipeline development
- Infrastructure-as-Code practices
- REST API development
- Identity and authentication frameworks
- Microsoft Azure and Kubernetes environments
- Containerized workloads
- Observability monitoring and telemetry systems
- Secure development lifecycle practices
- Secrets management and role-based access control
- Experience in regulated industries such as MedTech pharmaceuticals or manufacturing.
|
Mandatory Skills Powershell JD Key Responsibilities Automation Platform Development (Lite-Touch) Design and build a Lite-Touch Automation Platform that enables scalable workstation provisioning and configuration management. Responsibilities include: Architect and develop an enterpri...
| Mandatory Skills | Powershell |
| JD | Key Responsibilities Automation Platform Development (Lite-Touch) Design and build a Lite-Touch Automation Platform that enables scalable workstation provisioning and configuration management. Responsibilities include: - Architect and develop an enterprise automation framework enabling deterministic workstation configuration deployment
- Implement modular automation workflows supporting policy-driven configuration management
- Ensure 100% repeatable configuration outcomes
- Enable input-driven configuration provisioning using structured configuration inputs
- Integrate automation capabilities with enterprise request and service management platforms
- Implement logging traceability and auditability across automation workflows
- Manage configuration artifacts using version-controlled configuration management practices
- Eliminate configuration drift and manual build inconsistencies through automated enforcement
Configuration Quality Verification Platform Design and develop a Configuration Quality Verification Platform that validates workstation configurations against requested standards and enterprise quality policies. Responsibilities include: - Build automated verification workflows validating workstation configuration states
- Implement compliance validation aligned with enterprise quality standards
- Detect configuration drift and unauthorized configuration changes
- Verify alignment between requested and deployed configurations
- Generate automated reports and audit artifacts for regulatory compliance
- Enable engineering teams to perform automated quality assurance for workstation environments
Required Qualifications Professional Experience - 10 years of professional software engineering experience
- 5 years designing automation platforms or infrastructure automation systems
- Proven experience building enterprise automation frameworks or internal developer tools
- Strong DevOps engineering background
Programming - Advanced PowerShell automation and scripting frameworks
- C# / .NET application and platform development
Source Control & Engineering Practices - Git-based development workflows
- Branching strategies and pull request processes
- Code review and engineering quality practices
- Modern DevOps development methodologies
Artificial Intelligence Engineering Experience Hands-on experience integrating AI capabilities into development workflows working with: - Semantic Kernel
- Azure AI Foundry
- Comparable enterprise AI orchestration frameworks
Experience working with modern LLM ecosystems such as: - Anthropic Claude models
- Gemini models
- Microsoft Copilot models
AI Development Practices: - Prompt engineering
- AI-assisted development workflows
- Codex-driven development
- AI agent orchestration
Preferred Qualifications - Distributed systems design
- Automation platform architecture
- Modular framework development
- Event-driven systems
- CI/CD pipeline development
- Infrastructure-as-Code practices
- REST API development
- Identity and authentication frameworks
- Microsoft Azure and Kubernetes environments
- Containerized workloads
- Observability monitoring and telemetry systems
- Secure development lifecycle practices
- Secrets management and role-based access control
- Experience in regulated industries such as MedTech pharmaceuticals or manufacturing.
|
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