AI Platform Enablement Engineer III

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the assessment, prioritization, and controlled implementation of new features across enterprise AI platforms.

• Create rollout strategies, pilot groups, and comprehensive enablement methods.

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

• Develop, sustain, and enforce authorized usage patterns, platform guardrails, and usage limits.

• Coordinate execution of rollouts involving access provisioning, communications, and enablement activities.

• Define and monitor metrics for platform adoption, while addressing adoption challenges, configuration issues, and usability concerns.

• Identify both high-value and low-value usage patterns, and implement targeted adoption strategies.

• Collaborate with engineering and business stakeholders to capture measurable outcomes like efficiency improvements and delivery speed-ups.

• Maintain visibility into platform consumption, expenditure, and usage trends; analyze cost drivers and optimize platform utilization.

• Collaborate with Finance and IT leadership on budgeting and forecasting.

• Operationalize enterprise AI governance at the platform usage level, ensuring compliance with PHI and PII data protection standards.

• Establish practices for auditability and monitoring, coordinating with Security, Risk, Legal, and AI Governance stakeholders.

• Maintain configurations for feature enablement, reporting, and operational playbooks.

• Serve as the primary contact for platform evolution and vendor relations.

• Stay informed about platform capabilities and changes in the roadmap.

• Collaborate with architecture and engineering stakeholders to align platform usage with enterprise patterns and standards.

• Undertake other job-related tasks as assigned.

⛳️ Requirements

• Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline is required.

• Equivalent years of relevant work experience may be considered in place of the required education.

• A minimum of five (5) years of IT engineering experience, with at least three (3) years focused on DevOps, MLOps, or Cloud Infrastructure is required.

• Required experience with Azure AI Services (Azure OpenAI, AI Search, Azure ML) and container orchestration (Kubernetes/AKS).

• Proven experience in building and maintaining CI/CD pipelines for machine learning models or complex software applications is necessary.

• Familiarity with enterprise AI or advanced technology platforms is preferred.

• Strong understanding of AI/LLM capabilities and platform-based delivery models.

• Ability to manage the adoption, enablement, or rollout of enterprise technology platforms.

• Familiarity with consumption-based cost models and optimization strategies.

• Capability to work independently and lead initiatives in complex and uncertain environments.

• Knowledge of AI platforms such as Anthropic (Claude), Microsoft Copilot Studio, or Microsoft 365 Copilot.

• Awareness of AI governance, responsible AI practices, and regulatory considerations.

• Ability to operate within enterprise architecture or platform enablement functions.

• Exposure to usage analytics, reporting, and cost optimization frameworks.

• Microsoft Certified: Azure AI Engineer Associate or Azure DevOps Engineer Expert certification is preferred.

• CKA (Certified Kubernetes Administrator) certification is preferred.

🏝️ Benefits

• Bonus tied to company and individual performance may be available.

• Comprehensive total rewards package.

• Employee total well-being support.