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Salary
≈ $95k – $224k per year (Estimated)
Location
In office (Ireland)
Seniority
Staff
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 10, 2026. First seen by Alion on Aug 29, 2026. Mastercard scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Mastercard is a global payments technology company headquartered in Purchase, New York, operating the card network that connects consumers, merchants, banks and governments and providing data, cybersecurity, loyalty and open banking services. Founded in 1966 as the Interbank Card Association and listed on the New York Stock Exchange since 2006, it processes transactions in more than 200 countries and territories; this record is its UK domain, with major teams in London, Dublin, New York and Toronto. It hires software engineers, data scientists, AI engineering leaders, product managers, information security executives, regulatory counsel and program management interns.

Join Mastercard's AI Center of Excellence as a Lead AI Platform Engineer. In this role, you will lead the design, development, and evolution of the enterprise AI platform, manage a team of AI Engineers, and partner with various teams to deliver a secure and scalable AI ecosystem. You will also establish enterprise standards for MLOps and LLMOps, design cloud-native AI infrastructure, and drive platform reliability.

Missions

  • Lead the design, development, and evolution of the enterprise AI platform, ensuring it supports the full AI lifecycle from experimentation through production.
  • Manage and mentor a team of AI Engineers, providing technical guidance, coaching, performance feedback, and career development.
  • Define the technical roadmap for AI platform capabilities, ensuring alignment with business priorities and enterprise technology strategy.

Profil recherché

- Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field

- Experience leading and mentoring engineering teams in an enterprise environment

- Experience implementing security, governance, and compliance controls within enterprise technology platforms

- Strong understanding of platform engineering principles, DevOps, CI/CD, observability, reliability engineering, and automation

- Strong software engineering skills using Python

- Extensive experience designing and operating enterprise software platforms, cloud-native applications, or AI/ML platforms

- Experience building and operating AI/ML platforms, MLOps, or AgenticOps capabilities supporting production AI workloads

- Experience with modern AI technologies including LLMs, RAG, vector databases, model serving frameworks, and AI orchestration platforms

- Excellent communication, stakeholder management, and leadership skills

- Deep expertise with Kubernetes, Docker, APIs, microservices, Infrastructure as Code, and cloud platforms including AWS, Azure, or Google Cloud Platform

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