Director of AI/ML Platforms

Global Payments Inc.

. Execute the enterprise AI/ML platform strategy and multi-year roadmap .

Posted 10/19/2026full-timeAlpharetta • Ohio • United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in leading AI/ML platform strategies and operationalizing complex enterprise solutions, with a strong focus on model governance, compliance, and stakeholder management. Proven ability to enhance platform reliability and adoption through data-driven insights and cross-functional collaboration.

Highest-signal resume keywords

AI/ML Platform Strategy ExecutionMLOps ImplementationDatabricks ExpertiseModel Governance and ComplianceExecutive Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringCloud PlatformsData PlatformsPredictive Machine LearningGenerative AIModel DevelopmentLifecycle GovernanceInfrastructure AutomationKubernetesCI/CD

Soft Skills

LeadershipStakeholder InfluenceVendor ManagementTalent DevelopmentCross-Functional Collaboration

Tools & Technologies

MLflowAI GatewayCloud-Native AI ServicesAPIsDistributed SystemsSecure Model Access Patterns

Industry Keywords

AI Platform PortfolioOperational ExperienceModel Operations ControlsAudit TrailsCost Management

Tech Stack

Tools & technologies

CloudDistributed SystemsKubernetes

About the role

Key responsibilities & impact

Execute the enterprise AI/ML platform strategy and multi-year roadmap
Translate priorities from the Head of Data & AI Platforms into funded, sequenced, measurable platform outcomes
Lead delivery and reliable operation of the AI platform portfolio, including AI gateway, foundation model access, Databricks AI services, development workbenches, MLflow, MLOps, LLMOps, evaluation, observability, synthetic data, and agentic AI infrastructure
Run AI platform capabilities as internal products with service offerings, secure self-service journeys, architecture and engineering standards, SLAs/SLOs, support models, adoption measures, showback or chargeback transparency, and continuous improvement
Operationalize security, model governance, responsible AI, privacy, risk, legal, compliance, and audit requirements through automated controls
Build and lead an organization of AI platform engineers, MLOps engineers, technical product leaders, and partner resources
Manage delivery commitments, vendor relationships, budgets, talent development, and executive stakeholder communications
Collaborate across Data, AI, Engineering, Security, Architecture, Risk, Legal, Compliance, Infrastructure, and business teams
Improve platform outcomes, reliability, cost, risk, and adoption through data and feedback

Requirements

What you’ll need

U.S. citizenship or valid Green Card Holder status; position is not eligible for visa sponsorship now or in the future
Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field
10+ years of progressive experience in software engineering, cloud platforms, data platforms, AI/ML platforms, MLOps, or related technology disciplines
3+ years leading managers or senior engineering teams in a complex enterprise
Proven delivery and operational experience with enterprise AI/ML platforms supporting predictive machine learning and generative AI
Experience with model development, deployment, serving, registry, evaluation, monitoring, and lifecycle governance
Deep technical judgment across Databricks, MLflow, cloud-native AI services, Kubernetes and containers, APIs, CI/CD, infrastructure automation, distributed systems, and secure model access patterns
Experience implementing LLMOps and model operations controls, including model and prompt versioning, evaluation gates, observability, drift and quality monitoring, resiliency, access controls, audit trails, and consumption or cost management
Ability to lead platform products and teams in a regulated, matrixed environment
Experience with executive communication, financial management, vendor management, and stakeholder influence

Benefits

Comp & perks

Opportunities to learn, grow, and work across borders
Equal opportunity employment
Reasonable accommodations during the hiring process and employment
Drug testing for conditional U.S. offers