What are the responsibilities and job description for the Cloud AI Systems Administrator position at SMART TECH SKILLS LLC?
Benefits:
Location
Remote
Experience Level
Mid–Senior Level (5 or more years of cloud systems engineering experience, with 3 or more years in Microsoft Azure)
Role Overview
The Azure Cloud Engineer – AI & Automation administers, operates, and governs enterprise cloud infrastructure and artificial intelligence platforms within Microsoft Azure for a growing financial institution. Focused on cloud systems administration, security baselines, and operational guardrails rather than software development, this role ensures emerging AI technologies are deployed safely and transparently. Key responsibilities include configuring Azure AI Foundry, administering enterprise model integrations (Azure OpenAI, Anthropic Claude, Model Context Protocol / MCP), locking down data boundaries through Microsoft Purview, and maintaining automated CI/CD and Infrastructure-as-Code pipelines.
Key Responsibilities
AI Platform Administration & Governance
• Administer and operate enterprise AI platforms, including Azure AI Foundry, Azure OpenAI, OpenAI, and Anthropic Claude.
• Configure model parameters, access controls, quota policies, logging, and production deployment environments.
• Administer and govern Model Context Protocol (MCP) integrations, establishing authentication standards and secure data-handling boundaries between AI platforms and enterprise systems.
• Implement AI governance and responsible-use guardrails using Microsoft Purview, content filters, prompt and response inspection, and human-in-the-loop review workflows.
Cloud Infrastructure & Landing Zones
• Engineer, deploy, and maintain secure Azure landing zones across compute, networking, storage, and platform services in accordance with banking standards.
• Author and maintain Infrastructure as Code (IaC) templates utilizing Bicep, ARM, or Terraform to eliminate manual production configurations.
• Administer identity and access architectures leveraging Microsoft Entra ID, Conditional Access policies, managed identities, and Azure Key Vault.
• Govern cloud workloads using Azure Policy, role-based access control (RBAC), resource tagging, cost management, and Azure Monitor/Log Analytics.
Integration, APIs & Workflow Automation
• Configure, secure, and maintain API Management gateways, App Services, and Azure Functions connecting AI platforms to internal core systems.
• Support Retrieval-Augmented Generation (RAG) architecture implementations utilizing Azure AI Search, vector stores, and enterprise content indexes.
• Administer and govern Microsoft Fabric environments, overseeing workspace permissions, tenant settings, and workloads across Data Factory, Lakehouse, and Real-Time Analytics.
• Maintain operational automations built on Power Automate, Logic Apps, and Copilot Studio integrated with Microsoft 365, Teams, SharePoint, and ServiceNow.
Operations, Release Management & Compliance
• Build and maintain automated CI/CD pipelines in Azure DevOps and GitHub Actions for infrastructure and platform updates.
• Serve as a technical reviewer on the Change Advisory Board (CAB) for cloud and AI changes, ensuring compliance with banking regulatory controls.
• Document architectural reference patterns, standard operating procedures, pipeline templates, and operational runbooks.
• Track and report key performance indicators (KPIs) and key risk indicators (KRIs) regarding AI usage, platform health, and security boundaries.
Required Qualifications
• 5 or more years of experience in cloud systems engineering, systems administration, or infrastructure operations.
• 3 or more years of hands-on experience building, administering, and operating enterprise workloads within Microsoft Azure.
• Proven hands-on experience administering AI platforms (such as Azure AI Foundry, Azure OpenAI, Anthropic Claude, or OpenAI), including model configurations, access controls, and usage monitoring.
• Working knowledge of the Model Context Protocol (MCP) or equivalent AI integration patterns to govern system boundaries safely.
• Strong infrastructure-as-code proficiency authoring templates in Bicep, ARM, or Terraform, alongside CI/CD automation via Azure DevOps or GitHub Actions.
• Robust background in Azure identity, networking, and security governance (Entra ID, Key Vault, VNets, Conditional Access, and Zero Trust principles).
• Demonstrated scripting proficiency using PowerShell and Python for infrastructure and platform administration.
• Experience configuring and securing REST API gateways and event-driven services (Azure API Management, Event Grid, Service Bus).
• Bachelor's degree in Computer Science, Information Systems, or equivalent practical experience.
Preferred Qualifications
• Microsoft certifications such as Azure Administrator Associate (AZ-104), Azure Solutions Architect Expert (AZ-305), or DevOps Engineer Expert (AZ-400).
• Prior experience operating within financial services, banking, or other highly regulated environments subject to strict audit and risk controls.
• Hands-on experience administering Microsoft Fabric workspaces and capacity governance.
• Practical experience setting up RAG pipelines using Azure AI Search, vector databases, and evaluation frameworks.
• Experience managing MCP servers and integrating enterprise workflow tools (such as ServiceNow, Salesforce, or core banking engines).
• Familiarity with container platforms (Azure Kubernetes Service / AKS, Azure Container Apps).
Core Skills & Attributes
• Dedicated systems administration and infrastructure engineering mindset (focused on implementation, governance, and security rather than software development).
• Analytical approach to establishing enterprise guardrails, transparency, and data boundary controls for emerging AI technologies.
• Strong technical communication skills to articulate risks, governance options, and architectural tradeoffs to leadership and technical teams.
• High attention to operational rigor, compliance standards, and change management procedures.
- Competitive salary
Location
Remote
Experience Level
Mid–Senior Level (5 or more years of cloud systems engineering experience, with 3 or more years in Microsoft Azure)
Role Overview
The Azure Cloud Engineer – AI & Automation administers, operates, and governs enterprise cloud infrastructure and artificial intelligence platforms within Microsoft Azure for a growing financial institution. Focused on cloud systems administration, security baselines, and operational guardrails rather than software development, this role ensures emerging AI technologies are deployed safely and transparently. Key responsibilities include configuring Azure AI Foundry, administering enterprise model integrations (Azure OpenAI, Anthropic Claude, Model Context Protocol / MCP), locking down data boundaries through Microsoft Purview, and maintaining automated CI/CD and Infrastructure-as-Code pipelines.
Key Responsibilities
AI Platform Administration & Governance
• Administer and operate enterprise AI platforms, including Azure AI Foundry, Azure OpenAI, OpenAI, and Anthropic Claude.
• Configure model parameters, access controls, quota policies, logging, and production deployment environments.
• Administer and govern Model Context Protocol (MCP) integrations, establishing authentication standards and secure data-handling boundaries between AI platforms and enterprise systems.
• Implement AI governance and responsible-use guardrails using Microsoft Purview, content filters, prompt and response inspection, and human-in-the-loop review workflows.
Cloud Infrastructure & Landing Zones
• Engineer, deploy, and maintain secure Azure landing zones across compute, networking, storage, and platform services in accordance with banking standards.
• Author and maintain Infrastructure as Code (IaC) templates utilizing Bicep, ARM, or Terraform to eliminate manual production configurations.
• Administer identity and access architectures leveraging Microsoft Entra ID, Conditional Access policies, managed identities, and Azure Key Vault.
• Govern cloud workloads using Azure Policy, role-based access control (RBAC), resource tagging, cost management, and Azure Monitor/Log Analytics.
Integration, APIs & Workflow Automation
• Configure, secure, and maintain API Management gateways, App Services, and Azure Functions connecting AI platforms to internal core systems.
• Support Retrieval-Augmented Generation (RAG) architecture implementations utilizing Azure AI Search, vector stores, and enterprise content indexes.
• Administer and govern Microsoft Fabric environments, overseeing workspace permissions, tenant settings, and workloads across Data Factory, Lakehouse, and Real-Time Analytics.
• Maintain operational automations built on Power Automate, Logic Apps, and Copilot Studio integrated with Microsoft 365, Teams, SharePoint, and ServiceNow.
Operations, Release Management & Compliance
• Build and maintain automated CI/CD pipelines in Azure DevOps and GitHub Actions for infrastructure and platform updates.
• Serve as a technical reviewer on the Change Advisory Board (CAB) for cloud and AI changes, ensuring compliance with banking regulatory controls.
• Document architectural reference patterns, standard operating procedures, pipeline templates, and operational runbooks.
• Track and report key performance indicators (KPIs) and key risk indicators (KRIs) regarding AI usage, platform health, and security boundaries.
Required Qualifications
• 5 or more years of experience in cloud systems engineering, systems administration, or infrastructure operations.
• 3 or more years of hands-on experience building, administering, and operating enterprise workloads within Microsoft Azure.
• Proven hands-on experience administering AI platforms (such as Azure AI Foundry, Azure OpenAI, Anthropic Claude, or OpenAI), including model configurations, access controls, and usage monitoring.
• Working knowledge of the Model Context Protocol (MCP) or equivalent AI integration patterns to govern system boundaries safely.
• Strong infrastructure-as-code proficiency authoring templates in Bicep, ARM, or Terraform, alongside CI/CD automation via Azure DevOps or GitHub Actions.
• Robust background in Azure identity, networking, and security governance (Entra ID, Key Vault, VNets, Conditional Access, and Zero Trust principles).
• Demonstrated scripting proficiency using PowerShell and Python for infrastructure and platform administration.
• Experience configuring and securing REST API gateways and event-driven services (Azure API Management, Event Grid, Service Bus).
• Bachelor's degree in Computer Science, Information Systems, or equivalent practical experience.
Preferred Qualifications
• Microsoft certifications such as Azure Administrator Associate (AZ-104), Azure Solutions Architect Expert (AZ-305), or DevOps Engineer Expert (AZ-400).
• Prior experience operating within financial services, banking, or other highly regulated environments subject to strict audit and risk controls.
• Hands-on experience administering Microsoft Fabric workspaces and capacity governance.
• Practical experience setting up RAG pipelines using Azure AI Search, vector databases, and evaluation frameworks.
• Experience managing MCP servers and integrating enterprise workflow tools (such as ServiceNow, Salesforce, or core banking engines).
• Familiarity with container platforms (Azure Kubernetes Service / AKS, Azure Container Apps).
Core Skills & Attributes
• Dedicated systems administration and infrastructure engineering mindset (focused on implementation, governance, and security rather than software development).
• Analytical approach to establishing enterprise guardrails, transparency, and data boundary controls for emerging AI technologies.
• Strong technical communication skills to articulate risks, governance options, and architectural tradeoffs to leadership and technical teams.
• High attention to operational rigor, compliance standards, and change management procedures.
This is a remote position.