
Director of AI/ML Platforms
GLOBAL PAYMENT HOLDING COMPANY
Cincinnati, OH · HybridJobSeen 6 days agoSeen in employer's feed 6 days ago
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Job overview
The Director of AI/ML Platforms will execute the enterprise platform strategy and lead delivery and reliable operation of AI/ML platform capabilities. The role runs platform services as internal products, embeds security, governance, privacy, and compliance controls, and leads engineering teams, budgets, vendors, and executive communications. The position is hybrid, with three days per week in an office in Alpharetta, Georgia, or Cincinnati, Ohio.
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Full job description
Job Description This position is not eligible for visa sponsorship, now or in the future. Candidates must be a US Citizen or valid Green Card Holder. This position is hybrid 3 days per week in the following office locations: Alpharetta GA, Cincinnati, OH Ready to take your career global? Make your mark at one of the biggest names in payments. We're looking for a Director of AI/ML Platforms to join our ever-evolving Data & AI Platforms team and help shape the future of global commerce What you'll own - Execute the enterprise AI/ML platform strategy and multi-year roadmap, translating priorities established by the Head of Data & AI Platforms into funded, sequenced, measurable platform outcomes. - Lead delivery and reliable operation of the AI platform portfolio, including the AI gateway, foundation model access, Databricks AI services, development workbenches, MLflow model lifecycle capabilities, MLOps and LLMOps, evaluation, observability, synthetic data, and agentic AI infrastructure. - Run AI platform capabilities as internal products with clear service offerings, secure self-service journeys, architecture and engineering standards, SLAs and SLOs, support models, adoption measures, showback or chargeback transparency, and continuous improvement practices. - Operationalize security, model governance, responsible AI, privacy, risk, legal, compliance, and audit requirements through automated controls embedded in development, deployment, evaluation, and monitoring workflows. - Build and lead a high-performing 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. What you'll bring - Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field with 10+ years of progressive experience in software engineering, cloud platforms, data platforms, AI/ML platforms, MLOps, or related technology disciplines, including 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, including 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 such as an enterprise AI gateway. - Experience implementing LLMOps and model operations controls such as model and prompt versioning, evaluation gates, observability, drift and quality monitoring, resiliency, access controls, audit trails, and consumption or cost management. - Demonstrated ability to lead platform products and teams in a regulated, matrixed environment, with strong executive communication, financial and vendor management, stakeholder influence It's a bonus if you have Experience in payments, fintech, banking, or another highly regulated financial services environment, including support for model risk management, regulatory reviews, or audits. Experience with technologies such as Amazon SageMaker, Google Vertex AI, LiteLLM, Kubeflow, Fiddler, LangChain, LangGraph, OpenAI, Anthropic, Google Gemini, Tonic.ai, feature stores, retrieval-augmented generation, or AI agent orchestration. An advanced technical degree or relevant certification(s) in cloud architecture, AI engineering, machine learning, platform engineering, or security, plus experience buildin
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