AI Platform Enablement Engineer III

CareSource

. Own evaluation, prioritization, and controlled rollout of new capabilities across enterprise AI platforms .

Posted 10/8/2026full-timeRemote • United StatesMid-LevelSenior💰 $94,100 - $164,800 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing enterprise AI platform rollouts, including defining strategies, tracking adoption metrics, and ensuring compliance with data protection regulations. Proficient in optimizing platform usage and collaborating with cross-functional teams to drive measurable outcomes.

Highest-signal resume keywords

Enterprise AI Platform ManagementAzure AI Services ExperienceCI/CD Pipeline DevelopmentAI Governance KnowledgeDevOps/MLOps Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

DevOpsMLOpsCloud InfrastructureCI/CD PipelinesUsage AnalyticsCost OptimizationPlatform ConfigurationData Protection ComplianceContainer OrchestrationAI/LLM Capabilities

Soft Skills

Independent OperationLeadership in Ambiguous Environments

Tools & Technologies

Azure OpenAIAzure MLKubernetesMicrosoft 365 CopilotMicrosoft Copilot Studio

Certifications & Qualifications

Microsoft Certified: Azure AI Engineer AssociateAzure DevOps Engineer ExpertCKA (Certified Kubernetes Administrator)

Industry Keywords

Enterprise AIAI GovernanceRegulatory ConsiderationsConsumption-Based Cost ModelsPlatform Enablement

Tech Stack

Tools & technologies

AzureCloudKubernetes

About the role

Key responsibilities & impact

Own evaluation, prioritization, and controlled rollout of new capabilities across enterprise AI platforms
Define rollout strategies, pilot cohorts, and broad enablement approaches
Establish and manage role-based access, usage tiers, entitlement models, and 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 and resolve adoption blockers, configuration gaps, and usability friction
Identify high-value and low-value usage patterns and drive targeted adoption strategies
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 and optimize platform usage
Partner with Finance and IT leadership on budgeting and forecasting
Operationalize enterprise AI governance at the platform usage level and ensure compliance with PHI and PII data protection requirements
Establish auditability and monitoring practices and coordinate with Security, Risk, Legal, and AI Governance stakeholders
Maintain feature enablement settings, reporting configurations, and operational playbooks
Act as primary point of engagement for platform evolution and vendor interaction
Maintain awareness of platform capabilities and roadmap changes
Partner with architecture and engineering stakeholders to align platform usage with enterprise patterns and standards
Perform other job-related duties as requested

Requirements

What you’ll need

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
Familiarity 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
Knowledge of 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
Microsoft Certified: Azure AI Engineer Associate or Azure DevOps Engineer Expert preferred
CKA (Certified Kubernetes Administrator) preferred

Benefits

Comp & perks

Bonus tied to company and individual performance may be available
Comprehensive total rewards package
Employee total well-being support