Lead Product Manager - Genius AI Platform
About The Position
Global Payments is hiring a Lead Product Manager to own the shared AI platform foundation used by product teams across the company. The role sets platform strategy, makes build-versus-buy decisions, and validates ideas with working prototypes before teams commit engineering capacity. Rather than shipping a single feature, this position builds the foundation for multiple AI products. Its direct customers are product and engineering teams, and success is measured by the value those teams deliver to the businesses Global Payments serves. The position owns the multi-year platform vision and roadmap, core platform capabilities and standards, model portfolio and AI unit economics, and relationships with cloud and model vendors. It also establishes evaluation practices, responsible AI controls, production quality and reliability targets, and incident and rollback playbooks suited to a regulated payments environment. The role is hands-on: it builds customer-problem prototypes in one to two weeks without dedicated engineering support and documents their evaluation, cost, latency, and productionization considerations. It drives adoption and cross-functional alignment with product, engineering, architecture, security, legal, and risk teams; communicates platform direction to senior leaders; and mentors product managers as an individual-contributor leader.
Requirements
- At least 8 years of product management experience, with a meaningful share focused on technical, platform, or developer-facing products.
- Proven track record of shipping AI-powered products to production, including generative AI or agentic capabilities used by real customers rather than only pilots.
- Strong understanding of how LLM-based systems behave in production, including non-determinism, failure modes, and quality, cost, and latency trade-offs.
- Hands-on experience personally building and demonstrating working AI prototypes.
- Working proficiency in Python or a similar language, SQL, APIs, and JSON; comfort reading code, logs, and evaluation results.
- Practical experience with at least one major cloud AI platform.
- Track record of designing AI evaluation and guardrail approaches and using them to make release decisions.
- Proven ability to align senior stakeholders in a matrixed organization and write clearly for executives and engineers.
- Bachelor's degree in computer science, engineering, a quantitative field, or equivalent practical experience.
Nice To Haves
- Experience in payments, fintech, commerce, or B2B SaaS.
- Experience running multi-tenant AI in regulated environments, such as PCI DSS, SOC 2, or GDPR/CCPA.
- Experience shipping AI that takes actions in production systems with confirmation, undo, and audit controls.
- Experience building or governing a tool or integration catalog, including publishing and versioning standards.
- Experience with real-time or conversational AI, or on-device and edge AI.
- Experience with multi-cloud AI architecture.
- Patents, open-source contributions, publications, or talks on applied AI.
- Relevant cloud or AI certifications.
Responsibilities
- Define the multi-year vision and roadmap for a shared AI platform and make it the default path for teams building AI capabilities.
- Lead build-versus-buy-versus-partner decisions for core platform components, considering portability, vendor lock-in, cost, latency, and security.
- Own the model portfolio and AI unit economics, including routing rules, cost per interaction, and pricing inputs to the business.
- Manage cloud and model vendor relationships, including roadmap influence and commercial terms.
- Own platform building blocks such as orchestration, tools, workflows, connectors, and agents, and clarify when each pattern is appropriate.
- Define standards for exposing and integrating platform capabilities, including interfaces, schemas, error handling, permissions, and safe handling of data-changing actions.
- Own how context, memory, identity, and data access work across tenants and use cases.
- Build an evaluation practice combining offline test sets, automated and human review, production quality signals, and release gates.
- Own responsible AI guardrails and controls for a regulated payments environment, including data privacy, AI-specific security threats, grounding, action authorization, and auditability.
- Set production targets for quality, latency, availability, and cost, and own incident and rollback playbooks.
- Build working prototypes that take a customer problem to a demonstrable prototype in one to two weeks without dedicated engineering support.
- Ship each prototype with a small evaluation set, cost estimate, latency measurement, and note on productionization requirements; treat prototypes as decision evidence rather than production systems and maintain a record of problems, prototypes, and decisions.
- Drive platform adoption across product and engineering teams and run platform reviews with architecture, security, legal, and risk.
- Explain platform direction to senior leaders in plain language and write documents that align a multi-team program.
- Mentor other product managers on AI product practice as an individual-contributor leader.
Benefits
- Competitive salary and benefits package.
- Opportunities to grow skills and build a career within a global business.
- Access to learning, development, and on-the-job experiences.
- Supportive, inclusive team environment.
- Time to give back through community and charity initiatives.
- Global employee assistance program to support wellbeing.
- Recognition through a global platform that celebrates achievements.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
