AI Platform Enablement Engineer III

Job Summary:

The AI Platform Enablement Engineer III is responsible for the operational success of enterprise AI platforms by owning the end-to-end enablement, adoption, cost management, and governance execution of AI platforms, including but not limited to Anthropic (Claude), Microsoft Copilot Studio, and Microsoft 365 Copilot.

This role operates independently on complex and ambiguous problems, setting direction within its domain and ensuring that rapidly evolving AI platform capabilities are introduced in a controlled, value-driven, and governed manner. They do not own infrastructure or SRE operations but are accountable for platform enablement, configuration, and operational governance of usage.

Essential Functions: Own evaluation, prioritization, and controlled rollout of new capabilities, including pilot, scale, and deferment strategies, across AI platforms.

Define rollout strategies, including pilot cohorts and broad enablement approaches.

Establish and manage role-based access, usage tiers, entitlement models and related platform configurations.

Develop, maintain, and enforce approved usage patterns, platform guardrails and usage boundaries.

Coordinate rollout execution across access provisioning, communications, and enablement activities.

Define and track platform adoption metrics (e.g., active users, usage segmentation, engagement trends), identify and resolve adoption blockers, configuration gaps, and usability friction.

Identify high-value and low-value usage patterns across user cohorts.

Drive targeted adoption strategies to expand effective usage and reduce misaligned or low-value usage.

Partner with engineering and business stakeholders to capture measurable outcomes such as efficiency gains and delivery acceleration.

Own visibility into platform consumption, spend, and usage trends.

Analyze cost drivers across models, tools, and usage patterns.

Optimize platform usage through standardized patterns and model selection guidance.

Partner with Finance and IT leadership to support budgeting and forecasting.

Operationalize enterprise AI governance at the platform usage level.

Ensure compliance with data protection requirements, including PHI and PII constraints.

Establish and maintain auditability and monitoring practices.

Coordinate with Security, Risk, Legal, and AI Governance stakeholders to ensure alignment and compliance.

Maintain feature enablement settings and reporting configurations.

Develop and sustain operational playbooks for platform rollout and usage.

Act as the primary point of engagement for platform evolution and vendor interaction, providing structured feedback to vendors to influence roadmap alignment.

Maintain awareness of platform capabilities, roadmap changes, and enterprise impact.

Partner with architecture and engineering stakeholders to ensure platform usage aligns with enterprise patterns and standards.

Provide feedback into evolving design standards based on real-world platform capabilities and constraints.

Perform any other job related duties as requested.

• Education and Experience: Bachelor's degree in Computer Science, Software Engineering, or related technical field required
• Equivalent years of relevant work experience may be accepted in lieu of required education
• Five (5) years of IT engineering experience, with at least three (3) years specialized in DevOps, MLOps, or Cloud Infrastructure required
• Experience with Azure AI Services (Azure OpenAI, AI Search, Azure ML) and container orchestration (Kubernetes/AKS) required
• Experience building and maintaining CI/CD pipelines for machine learning models or complex software applications required
• Competencies, Knowledge and Skills: Familiarity with working with enterprise AI or advanced technology platforms
• Strong understanding of AI/LLM capabilities and platform-based delivery models
• Ability to manage adoption, enablement, or rollout of enterprise technology platforms
• Familiarity with consumption-based cost models and optimization strategies
• Ability to operate independently and lead initiatives in complex and ambiguous environments
• Knowledgeable in AI platforms such as Anthropic (Claude), Microsoft Copilot Studio, or Microsoft 365 Copilot
• Familiarity with AI governance, responsible AI practices, and regulatory considerations
• Ability to work within enterprise architecture or platform enablement functions
• Exposure to usage analytics, reporting, and cost optimization frameworks
• Licensure and Certification: Microsoft Certified: Azure AI Engineer Associate or Azure DevOps Engineer Expert preferred
• CKA (Certified Kubernetes Administrator) preferred
• Working Conditions: General office environment; may be required to sit or stand for extended periods of time
• Travel is not typically required