Lead AI Engineer at Mastercard

Mastercard operates in more than 200 countries and territories, supporting economies and empowering individuals and businesses worldwide.

Working alongside its customers, the company is committed to building a sustainable economy where everyone has the opportunity to prosper.

Through a broad range of digital payment solutions, Mastercard makes transactions secure, simple, intelligent, and accessible.

Its technology, innovation, partnerships, and global networks deliver products and services that help individuals, businesses, and governments achieve their full potential.

About the Role

Mastercard is looking for a Lead AI Engineer to join a small, specialized AI engineering team led by one of its Distinguished Engineers.

The team focuses on developing and scaling advanced AI technologies, particularly agentic systems such as the Model Context Protocol (MCP) and open-weight AI models.

This is a hands-on engineering position for someone who can design, develop, and deploy enterprise-grade AI infrastructure.

You will work closely with experienced engineers and technology teams across Mastercard to build secure, scalable platforms that support the organization’s adoption of modern AI technologies.

Your responsibilities will include developing systems that allow AI agents to securely access enterprise tools and data through MCP, as well as building the infrastructure required to deploy, evaluate, and manage open-weight models.

You will also contribute to important technical decisions involving security gateways, identity management, model deployment, and AI evaluation.

Key Responsibilities

• Help design and develop Mastercard’s enterprise MCP infrastructure, including security gateways, MCP registries, and reusable server implementations, taking solutions from initial design through production deployment.
• Implement authentication, authorization, and identity management systems that ensure AI agents, tools, and enterprise data can be accessed securely and monitored effectively.
• Establish standards for internal and external MCP servers, covering tool discovery, data access, version control, security inspections, data protection, rate limiting, and emergency shutdown capabilities.
• Develop and manage open-weight AI model infrastructure, including self-hosted inference systems, model packaging, and scalable deployment solutions.
• Build evaluation and testing frameworks to measure AI model performance across accuracy, cost, response time, and safety.
• Implement MLOps practices such as continuous integration and deployment (CI/CD), infrastructure-as-code, monitoring, and observability to maintain reliable production systems.
• Collaborate with security, privacy, legal, and AI governance teams to ensure platform solutions meet enterprise requirements.
• Work with technical working groups to evaluate emerging MCP developments, open-weight AI models, and other agentic technologies.
• Stay informed about advancements in artificial intelligence and identify technologies worth adopting, testing, or exploring.

Required Skills and Qualifications

• Strong understanding of modern AI technologies, including large language models (LLMs), foundation models, AI agents, and integration protocols such as MCP.
• Excellent software engineering skills, with the ability to develop reliable, well-tested, production-ready applications and services.
• Practical experience with MLOps, including CI/CD pipelines, infrastructure-as-code, containers, observability, and production monitoring.
• Good knowledge of cloud platforms, preferably AWS. Experience with Azure or Google Cloud Platform (GCP) is also valuable.
• Familiarity with modern data and AI platforms such as Databricks is an added advantage.
• Experience developing model evaluation frameworks and benchmarks to assess AI quality, cost, latency, and safety.
• Hands-on experience deploying and operating open-weight AI models, including self-hosting and scaling inference infrastructure.
• Knowledge of model fine-tuning or adapting AI models to proprietary data and business workflows is beneficial.
• Understanding of API security, identity management, authentication, and access control.
• Awareness of enterprise AI governance requirements, including model licensing, provenance, data sovereignty, and financial-services regulations.
• Strong communication and collaboration skills, with the ability to work effectively with engineers, security specialists, and governance teams.
• A strong interest in emerging technologies, particularly artificial intelligence, and the ability to learn quickly.
• Self-motivated, proactive, and capable of independently delivering technical solutions with minimal supervision

Salary and Benefits

Mastercard offers competitive compensation based on job location, relevant experience, technical knowledge, and qualifications.

Eligible employees may also receive annual bonuses or commissions, depending on the position.

Full-time employees generally have access to benefits that include:

• Medical, dental, vision, prescription, disability, and life insurance.
• Up to 16 weeks of paid parental leave.
• Up to 20 days of bereavement leave.
• 80 hours of paid sick and safe leave.
• 25 days of annual vacation and five personal days, prorated based on the date of hire.
• 10 paid U.S. public holidays.
• 401(k) retirement plan with company matching.
• Tuition reimbursement opportunities.
• Fitness reimbursement or access to on-site fitness facilities.
• Flexible spending and health savings accounts.

Application Deadline: Mastercard intends to fill this position by February 7, 2027. If the stated date has passed, the company plans to fill the vacancy as soon as possible.

Salary Range

The annual base salary varies by work location:

Location	Annual Salary
Purchase, New York	$161,000 – $266,000
Arlington, Virginia	$161,000 – $266,000
New York City, New York	$168,000 – $277,000
O’Fallon, Missouri	$140,000 – $231,000

Additional bonus or commission opportunities may apply, depending on the position.