AI Application Architect

SAIC•Washington, DC

7d•Hybrid

About The Position

The AI Application Architect provides end‑to‑end architectural leadership for AI‑enabled business solutions built on Microsoft Azure, Power Platform, and Microsoft Copilot Studio. This role defines reference architectures, technical standards, integration patterns, security and governance controls, and ensures that AI systems are scalable, compliant, and aligned to enterprise strategy. The architect partners with business units, engineering teams, and security stakeholders to translate organizational needs into modern, durable AI application ecosystems.

Requirements

End‑to‑end architectural leadership for AI‑enabled business solutions built on Microsoft Azure, Power Platform, and Microsoft Copilot Studio.
Define reference architectures, technical standards, integration patterns, security and governance controls.
Ensure AI systems are scalable, compliant, and aligned to enterprise strategy.
Partner with business units, engineering teams, and security stakeholders.
Translate organizational needs into modern, durable AI application ecosystems.
Leverage Azure AI, Azure OpenAI, Cognitive Services, Azure Machine Learning, and serverless compute.
Architect integrated AI agent ecosystems using Microsoft Copilot Studio.
Establish standards for prompt engineering, model selection, grounding data patterns, evaluation testing, and performance tuning of Copilot agents.
Design scalable, secure architectures for Power Apps, Power Automate, and Dataverse components.
Define solution boundaries, component interactions, managed solution structures, and DevOps release pipelines for Power Platform assets.
Architect integration solutions using Azure API Management, Logic Apps, Service Bus, Functions, and other PaaS components.
Define patterns for secure API exposure, private endpoints, identity‑based access (Managed Identities, service principals), and hybrid connectivity.
Align AI solutions with Azure‑based document processing, data analytics, and cognitive integrations.
Establish AI and Power Platform governance policies incorporating Zero Trust, connector restrictions, DLP boundaries, data residency, and RBAC role design.
Partner with cybersecurity and compliance teams to ensure alignment with PBGC governance frameworks.
Define operational guardrails for Copilot Studio environments.
Define data integration strategy for AI agents to safely and effectively consume enterprise data across Dataverse, Azure SQL, shared APIs, and external systems.
Develop patterns for enterprise data pipelines, event‑driven architectures, and data access zoning appropriate for AI governance.
Guide teams on using Azure Integration Services and cognitive services to enhance business workflows.
Serve as the primary architectural reviewer for AI, automation, and Power Platform projects.
Produce technical roadmaps, reference architectures, architecture decision records (ADRs), and design documentation.
Provide leadership and mentorship to AI developers, automation engineers, and business solution teams.
Ensure alignment with evolving enterprise IT modernization initiatives and platform strategies.

Responsibilities

Define enterprise‑level AI solution architectures leveraging Azure AI, Azure OpenAI, Cognitive Services, Azure Machine Learning, and serverless compute.
Architect integrated AI agent ecosystems using Microsoft Copilot Studio, including extensibility, action design, plugin behavior, data access strategy, and enterprise governance.
Establish standards for prompt engineering, model selection, grounding data patterns, evaluation testing, and performance tuning of Copilot agents.
Design scalable, secure architectures for Power Apps, Power Automate, and Dataverse components, including data modeling and environment segmentation.
Ensure Copilot‑enabled workflows integrate cleanly into Power Platform‑based applications and enterprise‑wide automation patterns.
Define solution boundaries, component interactions, managed solution structures, and DevOps release pipelines for Power Platform assets.
Architect integration solutions using Azure API Management, Logic Apps, Service Bus, Functions, and other PaaS components as shown in internal system architecture guidance.
Define patterns for secure API exposure, private endpoints, identity‑based access (Managed Identities, service principals), and hybrid connectivity.
Align AI solutions with Azure‑based document processing, data analytics, and cognitive integrations recommended in internal solution stacks.
Establish AI and Power Platform governance policies incorporating Zero Trust, connector restrictions, DLP boundaries, data residency, and RBAC role design.
Partner with cybersecurity and compliance teams to ensure alignment with PBGC governance frameworks, including runtime monitoring, model evaluation, and data protection expectations.
Define operational guardrails for Copilot Studio environments, including development, test, and production solution promotion workflows.
Define data integration strategy for AI agents to safely and effectively consume enterprise data across Dataverse, Azure SQL, shared APIs, and external systems.
Develop patterns for enterprise data pipelines, event‑driven architectures, and data access zoning appropriate for AI governance.
Guide teams on using Azure Integration Services and cognitive services to enhance business workflows, consistent with PBGC solution plans.
Serve as the primary architectural reviewer for AI, automation, and Power Platform projects.
Produce technical roadmaps, reference architectures, architecture decision records (ADRs), and design documentation.
Provide leadership and mentorship to AI developers, automation engineers, and business solution teams.
Ensure alignment with evolving enterprise IT modernization initiatives and platform strategies.