M

Mastercard

Processes payments across a global network

Lead AI Engineer

Applied Machine LearningPosted on Nov 9
Full-timeIn-person

About the Job

Requirements

  • Strong knowledge of modern AI technology, including large language models, foundation models, agents, and tooling and protocols such as the Model Context Protocol that connect them to enterprise systems.
  • Ability to write production-quality, well-tested code and build dependable services.
  • Solid MLOps experience with continuous integration and continuous delivery, infrastructure as code, containers, observability, and production monitoring for models and services.
  • Good cloud platform knowledge; AWS is preferred, and Azure or Google Cloud Platform experience is valuable.
  • Practical experience with model evaluation, including building benchmarks and tests that measure quality, cost, latency, and safety and produce reproducible results.
  • Hands-on experience serving or operating open weight models, self-hosting, and scaling inference; fine-tuning or adapting models to proprietary data and workflows is desirable.
  • Working knowledge of API security, identity, and access control sufficient to implement MCP authentication and authorization and partner with security teams.
  • Awareness of enterprise AI governance, including model provenance and licensing, data sovereignty, and financial-services regulation.
  • Ability to communicate and collaborate with senior engineers, hands-on peers, and governance and security partner teams.
  • Curiosity about technology and AI, learning agility, and the ability to work independently once given guidance and direction.
  • Responsibility for following security policies, protecting the confidentiality and integrity of accessed information, reporting suspected security violations or breaches, and completing mandatory security training.

Responsibilities

  • Design and build components of the enterprise MCP deployment, including the security gateway, MCP registry, and reference server implementations, taking them from design through production operation.
  • Implement identity, authentication, and authorization patterns for MCP across the estate with senior engineers and central security and identity teams, ensuring agent, tool, and data access is secure and auditable.
  • Set and apply standards for internal and external MCP servers, including how tools and data are exposed, discovered, and versioned, and controls for inspection, data protection, rate limiting, and kill switches.
  • Build and operate open weight model serving, including standing up and scaling self-hosted inference, packaging models for deployment, and enabling workload switching across models and providers.
  • Build evaluation and testing tooling to benchmark open weight models for quality, cost, latency, and safety and produce reproducible evidence for governance and security reviews.
  • Apply MLOps practices, including continuous integration and delivery, infrastructure as code, observability, and model and service monitoring, to keep the platform reliable and operable in production.
  • Partner with central security, privacy, legal, and AI governance teams, the MCP Special Interest Group, and the open weight working group to implement requirements in the platform architecture.
  • Track developments in MCP, open weight models, and agentic protocols, and help determine what to adopt, prototype, or defer.

Desired Qualifications

  • Experience with a modern data or AI platform such as Databricks.
  • Fine-tuning or adapting open weight models to proprietary data and workflows.

About the Company

Mastercard

Processes payments across a global network

Mastercard operates a global payment network connecting financial institutions, merchants, businesses and consumers. It authorizes, clears and settles transactions between participating institutions, while banks issue Mastercard-branded cards and extend credit to their customers. Its services also include fraud detection, identity verification, payment tokenization, data analysis and consulting for organizations managing commerce and financial operations. The company earns network fees linked to payment volumes and processed transactions, along with fees for its services and solutions. Founded by a group of banks in 1966, Mastercard is headquartered in Purchase, within Harrison, New York.

Company size
10,001+
Company stage
IPO
Headquarters
Town of Harrison, New York
Founded
1966

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