AI Platform Enablement Engineer III

CareSource; Dayton (OH); On-site; USD 94,000 - 165,000; Full time

Benefits offered by this job

Total rewards package

Bonus potential

Job summary

CareSource is seeking an AI Platform Enablement Engineer III to own end-to-end enablement, adoption, cost management, and governance for enterprise AI platforms, including Anthropic, Microsoft Copilot Studio, and Microsoft 365 Copilot. Role requires navigating complex problems independently and driving value-driven governance.

Responsibilities include rollout planning, access management, usage governance, adoption analytics, and collaboration with Finance, Security, and Legal to ensure

Qualifications

• Bachelor's degree in CS, SE, or related field.
• 5 years IT engineering with at least 3 years in DevOps, MLOps, or Cloud Infra.
• Experience with Azure AI Services and Kubernetes/AKS.
• Experience building and maintaining CI/CD pipelines for ML models or complex apps.

Responsibilities

• Own end-to-end enablement and governance of AI platforms.
• Define rollout strategies and adoption metrics.
• Manage access, usage tiers, and platform guardrails.
• Coordinate with Security, Legal, and Governance stakeholders.
• Analyze cost drivers and optimize platform usage.
• Partner with Finance and IT for budgeting and forecasting.
• Develop operational playbooks for platform rollout.

Skills

DevOps

MLOps

Azure AI Services

Kubernetes / AKS

CI/CD pipelines

Cloud Infrastructure

Education

Bachelors in Computer Science or related field

Tools

Azure AI Services (Azure OpenAI, AI Search, Azure ML)

Kubernetes/AKS

Job description

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.

• 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

Compensation Range:

$94,100.00 - $164,800.00

CareSource takes into consideration a combination of a candidate’s education, training, and experience as well as the position’s scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. In addition to base compensation, you may qualify for a bonus tied to company and individual performance. We are highly invested in every employee’s total well-being and offer a substantial and comprehensive total rewards package.

Compensation Type (hourly/salary):

Salary

Organization Level Competencies

• Fostering a Collaborative Workplace Culture

• Cultivate Partnerships

• Develop Self and Others

• Drive Execution

• Influence Others

• Pursue Personal Excellence

• Understand the Business

This job description is not all inclusive. CareSource reserves the right to amend this job description at any time. CareSource is an Equal Opportunity Employer. We are dedicated to fostering an environment of belonging that welcomes and supports individuals of all backgrounds.