Posted: 2h ago
The role
Director, Product Management - AI Platform
Director, Product Management - AI Platform
Description: The Director of Product Management is responsible for defining and delivering the product strategy, roadmap and outcomes for an enterprise, cloud‑native AI platform that enables a federated data mesh across the organization. This platform serves as the foundation for analytics, AI/ML, data products and data commercialization use cases at scale.
Define and evolve the product vision and strategy for the enterprise AI platform.
Articulate a clear target state for the platform, aligned to enterprise data, analytics and AI strategies.
Translate business and domain needs into scalable platform capabilities and services.
Own the platform product roadmap, prioritising capabilities such as data ingestion and integration, lakehouse and analytical storage, orchestration frameworks, platform SLOs, reliability engineering, usage analytics, cost attribution and chargeback.
Balance near‑term delivery with long‑term architectural integrity and scalability.
Enable domain teams to operate as data product owners by providing clear standards, tooling and self‑service capabilities.
Partner with Data Governance to embed federated governance and policy enforcement into the platform.
Partner with Engineering to translate product requirements into executable technical plans.
Collaborate with Product Operations on adoption, enablement and customer experience.
Work with Architecture, Security, Legal and Risk teams to ensure platform compliance and resilience.
Influence without direct authority across distributed, global teams.
Ensure AI capabilities are delivered with a strong focus on quality, reliability and readiness for enterprise‑scale launch.
Define success metrics and ensure outcomes align to business and platform goals.
Drive continuous improvement through customer feedback, usage insights and performance data.
Serve as the primary product leader and evangelist for the AI products.
Build strong relationships with senior executives and domain leaders.
Communicate platform value, roadmap progress and outcomes in clear, executive‑ready language.
Proven experience in Product Management, with significant experience leading enterprise platform products.
Proven experience building or scaling cloud‑native data platforms or large‑scale analytics platforms.
Deep understanding of data mesh concepts, including domain ownership, data products, federated governance and self‑service infrastructure.
Experience with modern data technologies and ecosystems: AWS, Azure, GCP; lakehouse and analytics platforms such as Databricks and Snowflake; streaming, APIs and event‑driven architectures.
Strong analytical and systems‑thinking skills.
Experience in highly regulated industries such as financial services, payments or healthcare is a plus.
Familiarity with AI/ML platforms and data‑driven product development.
Experience working in global, matrixed organizations.
Strategic thinker with a strong bias toward execution.
Excellent communication and storytelling skills, including executive‑level presentations.
Ability to navigate ambiguity and drive alignment across diverse stakeholders.
Strong people‑leadership experience, including mentoring and developing senior product managers.
Customer‑centric mindset with empathy for technical and non‑technical users.
Product Management, Director - Partnerships Onboarding
Director – Partnerships Onboarding
This role focuses on enabling SME products to scale with confidence, defining how partner onboarding works today and for the future, supporting growth and meeting governance and regulatory expectations.
Own the end‑to‑end SME onboarding framework, including processes, tooling, metrics and governance.
Design scalable operating models that balance fast time‑to‑market with strong risk and compliance discipline.
Align cross‑functional teams – product, risk, sourcing, legal, security and regional stakeholders – around onboarding priorities.
Prioritise onboarding enhancements based on SME impact, risk exposure and scalability.
Lead resolution of complex onboarding challenges, escalations and risk decisions.
Translate regulatory and policy requirements into clear, SME‑appropriate standards.
Provide senior leadership with visibility into onboarding health, capacity, performance and risk trends.
Build, coach and lead a high‑performing onboarding team (L8 / L7), setting clear expectations and development paths.
Bachelor’s degree or equivalent practical experience.
Significant experience in product management, operations, risk, compliance or governance‑focused roles.
Background in partnership‑driven or ecosystem‑based models (SMEs, fintech, platforms, marketplaces).
Proven ability to influence senior stakeholders and align diverse teams.
Strong strategic thinking paired with disciplined execution.
Director of AI Engineering
Director of AI Engineering leads a specialized team focusing on foundation model development and delivery of high‑value AI use cases, ensuring models are developed, adapted and deployed to solve real business problems.
Lead a team of AI engineers focused on foundation model development, fine‑tuning and optimisation.
Drive end‑to‑end delivery of AI use cases from problem definition through model integration and production deployment.
Partner with product and business stakeholders to identify and prioritise high‑impact AI use cases and translate them into clear technical execution plans.
Ensure effective use of foundation models across use cases, including prompting strategies, embeddings, fine‑tuning, evaluation and performance optimisation.
Collaborate with data engineering and platform teams to ensure data readiness, model integration and scalable deployment patterns.
Embed responsible AI practices, including model validation, bias considerations and appropriate guardrails.
Track delivery progress, manage risks and ensure timely, high‑quality execution of use cases aligned to program priorities.
Proven experience leading teams delivering AI/ML solutions in production, particularly use‑case driven environments.
Strong hands‑on understanding of transformer architectures and generative AI, including fine‑tuning, prompting, embeddings and evaluation.
Experience bridging model development and real‑world application, translating AI capabilities into business impact.
Solid engineering background with familiarity in Python, ML frameworks such as PyTorch/TensorFlow and production deployment patterns.
Experience working with data engineering and MLOps practices to support training, evaluation and inference at scale.
Strong stakeholder management skills, aligning technical delivery to business priorities and measurable outcomes.
Demonstrated ability to lead and develop high‑performing teams, providing technical direction and coaching.
Excellent communication skills, able to articulate complex AI concepts to technical and non‑technical audiences.
Director, Technical Program Management
Director, Technical Program Manager focuses on building and operating the Cross‑Border payments platform within the Treasury Management domain, driving engineering build and ensuring alignment across stakeholders.
Plan, oversight and end‑to‑end delivery of work for globally distributed engineering teams.
Prioritise and manage dependencies, remove impediments and support teams in solving complex challenges.
Collaborate with Treasury, Finance, Product and vendor teams to ensure alignment, manage change and risk.
Manage a small group of other TPMs working on the same portfolio.
Independent and autonomous, with experience breaking down problems, organising work, planning sprints and delivering technical programmes.
Experience in agile delivery models (scrum, Kanban).
Strong analytical and data‑driven decision making, continuous improvement mindset.
Experience communicating and influencing senior stakeholders and distributed teams.
Prior technical management experience a plus.
BS in engineering, computer science, project management or related discipline.
Manager, Product Development
Manager – Product Development oversees product development for Mastercard’s Next Gen Network initiatives, delivering scalable products for commercialization under the Network Solutions program.
Integrate business applications at enterprise level, design and implement custom interfaces and mapping.
Define application integration requirements and lead multi‑tier integration initiatives.
Own epic, feature and story elaboration for assigned initiatives.
Ensure integrity and consistency of delivery across all products.
Produce artefacts such as sequence diagrams, capability training decks, API articles and product guides.
Intermediate software engineering knowledge, experience with Agile methodology, full‑stack application design.
Experience in prioritisation, backlog grooming, iteration planning and stakeholder engagement.
Knowledge of ISO 20022 and ISO 8583 messaging standards is an advantage.
Senior Product Manager – Technical
Senior Product Manager – Technical provides technical platform enablement across AI & Decisioning Platform Enablement (AI & DPE), translating complex technical capabilities into scalable business solutions.
Serve as main liaison for AI & DPE market‑facing products and business integration.
Actively elicit feedback, manage escalations and maintain transparency with stakeholders.
Bridge AI & DPE business stakeholders with technology teams to align roadmaps, release plans and prioritization outcomes.
Facilitate collaboration across product, business integration and leadership teams to maintain visibility on roadmaps and demand.
Define, elaborate and prioritize initiatives, including feasibility analysis and business case development.
Track delivery progress, manage risks and ensure value realization through demos, UAT and feedback loops.
Proven experience as product manager or product leader with focus on technical platforms, ideally within AI, data or decisioning domains.
Strong understanding of modern technology practices (APIs, microservices, cloud, data platforms).
Strong stakeholder management skills and ability to align technical capabilities with business objectives.
Excellent communication skills, articulated to technical and non‑technical audiences.
Experience coaching technical product managers and leading teams.
Bachelor’s degree in Computer Science, Engineering, Business or related field.
Senior Product Specialist – SME Partner Enablement
Senior Product Specialist focuses on enabling SME partners to bring products to market faster, leading day‑to‑day onboarding and risk management for partner portfolios.
Own onboarding delivery from initiation through approval and launch readiness.
Act as primary onboarding point of contact for SME product teams and external partners.
Proactively manage risks, dependencies and cross‑functional blockers.
Guide partners through onboarding, remediation and documentation requirements.
Identify recurring friction points and recommend standardisation, simplification or automation.
Create and maintain onboarding playbooks, templates and FAQs.
Provide clear updates and insights to leadership based on data.
Mentor Product Specialists, driving execution quality and SME operational maturity.
Bachelor’s degree or equivalent experience.
Experience in product operations, partner enablement, risk, compliance or governance‑focused roles.
Experience working with partners of varying size and complexity.
Strong stakeholder management, problem‑solving and decision‑making skills.
Comfortable operating autonomously in fast‑paced, partnership‑led environments.
Product Specialist – SME Third‑Party & Partnership Operations
Product Specialist manages end‑to‑end onboarding execution for SME ecosystem partners, vendors and service providers, ensuring risk, due diligence and operational requirements are met.
Coordinate risk and due diligence activities, including documentation collection and alignment across teams.
Track progress, risks, dependencies and timelines across multiple partners.
Maintain high‑quality onboarding artifacts: trackers, dashboards and standardised documentation.
Apply standard onboarding frameworks while adapting to different SME business models.
Support remediation and issue resolution, driving follow‑ups and evidence tracking.
Bachelor’s degree or equivalent experience.
Experience in product operations, partner operations, vendor management, compliance or sourcing.
High attention to detail and effective stakeholder communication.
Principal AI Engineer
Principal AI Engineer leads the design, build and scaling of production‑grade AI systems, driving technical direction and mentorship across AI teams.
Design, implement and operate advanced AI systems supporting critical business and client needs at scale.
Partner with product, engineering and data leaders to translate business intent into robust AI architectures.
Provide mentorship, technical leadership and influence across teams without formal line management.
Demonstrated experience designing and building AI/ML production systems at scale.
Expert proficiency in Python, PyTorch and TensorFlow.
Strong experience with cloud‑native AI architectures on AWS, Azure or GCP.
Deep knowledge of machine learning, deep learning, NLP, generative AI and transformer‑based architectures.
Proven expertise in MLOps: model versioning, deployment, monitoring, evaluation and lifecycle management.
Strong systems‑thinking, experience with large‑scale data architectures and optimisation.
Excellent communication skills, translating complex technical concepts to diverse audiences.
Lead AI Engineer
Lead AI Engineer drives hands‑on delivery of applied AI and agentic capabilities across platforms, influencing technical direction and partnering with data science and product teams.
Lead preparation of AI and agentic systems from design to production deployment.
Build and operate ML/AI services, pipelines and APIs using strong software engineering practices.
Design and implement model serving, monitoring, evaluation and retraining capabilities.
Collaborate with data scientists to productionise models and experiments.
Engage platform, security and infrastructure teams to ship responsibly at scale.
Strong experience as an AI engineer, ML engineer or senior software engineer in production AI systems.
Solid foundations in software engineering, system design and distributed systems.
Proven productionising of machine learning models at scale.
Comfortable working across data engineering, ML engineering and applied data science.
Experience with large‑scale data platforms and modern ML/AI tooling.
Strong problem‑solving, ability to work with ambiguous requirements.
Ability to influence technical direction without formal people management.
Clear communication skills and comfort collaborating across functions.
Track record of raising the technical bar for teams through code, design and mentorship.
Corporate Security Responsibility
Abide by Mastercard's security policies and practices.
Ensure the confidentiality and integrity of the information being accessed.
Report any suspected information security violation or breach.
Complete all mandatory security trainings in accordance with Mastercard's guidelines.
Equal Opportunity Statement
Mastercard is a merit‑based, inclusive, equal‑opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disability or veteran status or any other characteristic protected by law. We hire the most qualified candidate for the role.
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