Description/Responsibilities

Our Senior AI Implementation Engineer is a hands-on role focused on partnering with business leaders and internal teams to design, build, and deploy AI agents and Copilot solutions in Microsoft 365 that drive measurable productivity and business outcomes. This role bridges AI engineering, enablement, and operations—building foundational and shared agents directly while also coaching business teams to design, build, and own agents of their own.

This position is centered on applied generative AI, using Microsoft 365 Copilot, Copilot Studio, and the broader Microsoft AI ecosystem to rapidly validate ideas, embed agents into business workflows, and ensure they are reliably running and adopted by internal teams.

Business-Driven Experimentation & Agent Delivery

Partner directly with business stakeholders across departments to identify workflows where AI agents and Copilot can improve productivity, decisions, or outcomes
Design experiments and pilots that can be validated quickly using available Microsoft 365 data sources and pragmatic agent-building approaches
Select and apply the right Copilot capabilities for each use case (declarative agents, custom actions, plugins, Copilot Studio agents, Power Automate flows)
Build and deliver high-impact and shared agents directly when central ownership makes sense; enable business teams to own their own agents end-to-end when distributed ownership is a better fit—coaching them through grounding data preparation, prompt design, deployment, monitoring, and iteration

AI Agent Implementation, Production & Operations

Build and deploy custom Copilot agents using Copilot Studio, declarative agents, and the Microsoft 365 Agents SDK; integrate them into Teams, Outlook, Word, Excel, and SharePoint experiences
Implement agent grounding pipelines using Microsoft Graph connectors, SharePoint, OneDrive, and structured data sources
Ensure production readiness for both centrally built and business-built agents through versioning, validation, rollback strategies, and performance monitoring standards
Monitor performance of central agents directly (response quality, grounding accuracy, adoption, business KPIs); equip business owners with the dashboards and patterns to monitor theirs
Participate directly in diagnosis and resolution of production issues affecting Copilot agents or supporting integrations, regardless of who built them

Enablement, Training & Internal Team Collaboration

Teach and coach internal teams on how to design, build, refine, and operate their own Copilot agents and prompts
Create reusable templates, patterns, and reference implementations that accelerate agent delivery across the organization
Develop training materials, office hours, and hands-on workshops that scale Copilot adoption beyond the central team
Collaborate closely with IT, Security, and Compliance teams to align with enterprise data protection, DLP, and operational standards
Use source control and infrastructure as code (GitLab/GitHub, Pulimi) to manage agent definitions, environments, and deployment pipelines—and make those practices accessible to citizen builders

Governance, Content Architecture & Operational Excellence

Own and operate Microsoft Graph and SharePoint-based grounding sources for Copilot agents, including connectors, content indexing, and semantic indexing
Implement and enforce content zone architecture (e.g., authoritative, curated, and restricted sources) to support governed agent grounding and lifecycle management for both central and business-owned agents
Define and apply access controls using sensitivity labels, Microsoft Purview, and Microsoft 365 permissions
Establish and maintain governance practices around prompt libraries, agent definitions, version control, and lineage tracking that apply consistently across the organization
Ensure agents and their grounding sources are discoverable, auditable, and secure through cataloging, metadata management, and access controls
Build end-to-end observability using Microsoft 365 admin telemetry, Copilot analytics, Purview audit logs, and adoption dashboards
Establish operational runbooks and support procedures for governed Copilot agents and AI workflows

Cost-Effective, Scalable AI Delivery

Apply cost-aware design when selecting agent architectures, grounding sources, and Azure AI services
Optimize Copilot Studio capacity, message usage, and Azure OpenAI consumption to deliver value efficiently at scale
Continuously improve agent reliability, scalability, and cost efficiency as adoption grows across both central and business-owned agents

AI Center of Excellence (CoE) Partnership

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