Architect – AI Business Solutions

Understanding Customer Technical Environment 

• Engage business sponsors, product owners, Enterprise Architects, Security, and Operations leaders to frame outcomes and define the target agentic scenarios.  

• Assess customer AI readiness across identity, data, security/compliance, and operating model; identify gaps to unlock Copilot and agent adoption at scale.  

• Identify industry and technology trends including AI adoption patterns, Low‑Code modernization, Copilot usage, GitHub Copilot assisted development, and data readiness to influence solution architecture direction. 

• Translate business requirements  into end-to-end solution options across Power Platform, Azure, and Microsoft 365 Copilot/Copilot Studio extensibility. 

• Socialize solution approaches with customers, validating feasibility, operating impact, scalability, and change management required for Copilot and agent rollouts. 

• Maintain an iterative feedback loop with Product Engineering and internal communities to relay field insights that shape M365 Copilot, Copilot Studio, Power Platform capabilities for agentic engagements. 

• Partner with account and delivery teams to shape the solution play, refine estimates, adjust pre‑sales solution components, govern scope changes, and position technical risks for agentic AI adoption. 

Architecture Design and Deployment 

• Apply structured delivery methodologies (Agile/Iterative/Hybrid) and reference architectures to design scalable Copilot and agentic solutions. 

• Own and maintain architectural documentation, including agent design specs, integration contracts, and operational runbooks. 

• Define and communicate end-to-end architecture with traceability from business outcomes to agent behaviors, tools, data grounding, quality attributes, and compliance controls. 

• Lead cost- and technology-based discussions to assess feasibility, deployment options (cloud/edge), scale, and customer appetite for agentic innovation. 

• Apply business value principles prioritizing ROI, productivity, adoption/usage intensity, and long-term operational efficiency. 

• Partner with the Project Manager to drive governance across design, build, testing, deployment, pilots, and scale-out of Copilot and agent capabilities. 

• Validate delivered business value (revenue enablement, productivity uplift, customer/employee experience improvement, cost savings) and connect outcomes to telemetry and adoption signals. 

• Direct development and execution of test strategies (functional, security, privacy, and AI evaluations) to prove requirement compliance and support remediation and sign-off. 

• Collaborate with bid teams to prepare costed, traceable solution approaches with trade-offs, AI risk posture, and clear positions on responsible AI. 

• Lead implementation with the Project Manager, establishing quality standards, release planning, and operational transition for agentic workloads. 

• Highlight invalidated assumptions and drive refinements through structured change control and continuous learning from production usage. 

AI, Copilot, LowCode, and Agent Extensibility 

• Establish enterprise-grade architecture to support scaled Copilot and agent deployments. 

• Design  Copilot extensibility solutions with secure data access patterns and clear user/agent experience flows.  

• Use Copilot Studio to build and manage agents (topics/actions, orchestration, channels, monitoring) for customer productivity improvement and business process transformation. 

• Apply GitHub Copilot to accelerate engineering, enforce secure coding and quality, and improve delivery velocity for agentic solutions. 

Practice Development 

• Continuously evaluate and evolve architectural approaches based on field learnings, product roadmap, and responsible AI guidance to maintain a high quality IP portfolio. 

• Drive reuse of IP across pre-sales and delivery to accelerate pipeline, improve quality, and standardize agentic delivery practices. Drive reuse of IP across pre‑sales and delivery engagements. 

• Contribute to internal and external Microsoft professional communities by sharing patterns, learnings, and reusable agent/Copilot assets. 

Trusted Advisor 

• Build strong networks and influence across customer and internal teams to remove barriers and accelerate Copilot and agent adoption. 

• Stay current on Microsoft’s AI Business Solutions strategy and communicate platform direction across M365 Copilot, Copilot Studio, Power Platform, and Azure. 

• Act as the technical conscience balancing customer expectations with feasibility, security, privacy, and responsible AI practices. 

Thought Leadership 

• Share insights, reusable patterns, and strategic guidance for Copilot and agentic architectures across global communities. 

• Mentor technical talent on agentic design patterns, Power Platform governance, Copilot extensibility, and responsible AI engineering.  

PreSales 

• Discover customer priorities and pain points to shape Copilot and agentic solution plays that deliver measurable business outcomes. 

• Propose architectures and roadmaps with clear assumptions for data readiness, identity/permissions, integrations, and AI risk controls. 

• Support Sales teams in winning and expanding enterprise engagements by leading with Copilot and Agents as the transformation entry point. 

• Own technical estimates and delivery approach for agentic engagements using proven, experience‑based estimation methods and reusable accelerators. 

Solution Delivery 

• Guide Low‑Code / No‑Code AI  adoption across Power Platform and Copilot-‑enabled development to accelerate business process transformation. 

• Lead governance and deployment of Copilot Studio agents ensuring security, responsible AI, connector controls, and data boundary alignment. 

• Deliver custom Microsoft 365 Copilot extensions using approved SDKs, plugins/connectors, automation frameworks, and secure data access patterns. 

• Apply engineering excellence and DevOps practices (CI/CD, quality gates, automation, observability) using Azure DevOps and GitHub. 

• Guide sprint/iteration planning, dependency mapping, and end‑to‑end release alignment to move from pilots to scaled production adoption. 

Quality Assurance 

• Review solutions for requirement fidelity, security/privacy posture, responsible AI compliance technical quality, best‑practice alignment, and operational readiness 

• Provide  advisory guidance for Copilot and agent architecture, design, and delivery execution. 

• Enforce best practices for Copilot Studio agent lifecycle management, grounding strategies, evaluations, and monitoring for continuous improvement .