Join Mastercard as an AI-First Technical Program Manager dedicated to accelerating delivery across agent-amplified pods. You will be instrumental in maintaining specifications as the single source of truth and utilizing DORA/Core4 metrics as key performance indicators for delivery. This role acts as a crucial connective point within a shared pool, ensuring program coordination, risk assessment, and dependency management are current without micromanaging daily tasks, all while preserving critical SOX/PCI control gates. We track manifest definitions, release integration, scope, and dependencies using data to ensure all outputs are production-ready from launch.

Orchestrate and accelerate technology projects across multiple pods, fostering alignment among dependent organizations. Proactively identify and remove obstacles, consistently charting a path forward. Develop detailed pod-to-pod relay plans, aggregate cross-functional risks and dependencies into a unified view, and drive execution through the monthly Epic cycle, guided by user documentation. Serve as the primary source for status updates, generating essential reports like the Monthly Technical Review (MTR), RAID Log, and DORA rollup directly from session records using M365 Copilot to maintain an up-to-date ledger.

Continuously enhance and streamline processes, eliminating unnecessary ceremony. Clearly define the reviewer for every artifact before its retention and deliberately retire outdated ceremonies. Stay informed about the evolving AI engineering landscape, understanding AI's capabilities and limitations, and how it amplifies engineering judgment. Ask critical questions to evaluate scalability, latency, security, performance, and data integrity. Navigate ambiguity with minimal guidance, embrace the dynamic nature of agent-driven delivery, and remain grounded by monthly user guides and real customer feedback.

Transform abstract concepts into clear, concise communications, confidently engaging stakeholders at multiple levels. Master prompt patterns and agent session discipline to produce review-ready output efficiently. Understand the specific needs of engineers and BizOps/SRE teams, including the verification overhead and follow-the-sun pairing strategies. Review metrics diligently, actively seeking improved data and visibility mechanisms to align programs with objectives while upholding all control gates. AIFE is designed to reduce coordination overhead, not compromise controls. Play a significant role in mentoring, recruiting, and developing agent fluency and the Expert-Generalist skill ladder across pods.

Anticipate potential bottlenecks and incorporate contingency plans for unforeseen delays, including managing the transition risk from Scrum to the pod model. Define success metrics where they are currently absent, defaulting to the four DORA/Core4 metrics: Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Failed Deployment Recovery Time. Effectively recognize and resolve conflicting viewpoints through constructive dialogue, acting as the program's confirmation bias safeguard. Continuously evaluate development processes, test plans, and operational procedures to enhance concurrent delivery, incorporating strategies like tests-first/spec-driven parallelism and maintaining real-time documentation currency. Streamline or eliminate redundant processes that are repeatedly addressed year after year. Possess expert-level knowledge of Scrum delivery and its evolution into the AIFE monthly Epic and pod-relay operating model, including the shift from story points to spec-projected slices.

Demonstrate fluency with AI-First Tooling & Skills, including M365 Copilot proficiency across Excel (RAID Log, dependency matrix, DORA dashboards), Word (MTR generation, handoff notes), and Loop/OneNote (async session logs). Adhere to the spec-as-ledger discipline, treating specifications as reviewed engineering work and leveraging agents to project epic/feature/story records on demand rather than manual slicing or pointing. Effectively manage the relay and shared-pool operating model, charting pod relays, handling follow-the-sun handoffs, and guiding progress based on feedback at Epic boundaries. Ensure agent accountability and audit-safety by verifying that a named human directs and reviews all agent outputs, maintaining session logs and control-role sign-offs for auditable tracking of who built and who approved.