Lead AI Platform Engineer — Scale Enterprise AI

MasterCard; Dublin; On-site; EUR 120,000 - 180,000; Full time

Job summary

Mastercard seeks a Lead AI Platform Engineer to guide the design, development, and evolution of its enterprise AI platform, enabling teams to build, deploy, and operate AI and Generative AI solutions at scale.

You will manage AI engineers, define roadmaps, and partner across Architecture, Cloud, Data, Security, Product, and Data Science to deliver secure, scalable AI services enterprise-wide.

Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
• Extensive experience designing and operating enterprise software platforms, cloud-native applications, or AI/ML platforms.
• Experience leading and mentoring engineering teams in an enterprise environment.
• Strong software engineering skills using Python
• Deep expertise with Kubernetes, Docker, APIs, microservices, IaC, and cloud platforms including AWS, Azure, or Google Cloud Platform.
• 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.
• Strong understanding of platform engineering principles, DevOps, CI/CD, observability, reliability engineering, and automation.
• Experience implementing security, governance, and compliance controls within enterprise technology platforms.
• Excellent communication, stakeholder management, and leadership skills.

Responsibilities

• Lead the design and evolution of Mastercard's enterprise AI platform, providing reusable services, tools, and frameworks that accelerate AI solution delivery
• 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
• Build and maintain shared AI services including model serving, inference APIs, feature stores, vector databases, prompt management, AI gateways, model registries, and developer self-service capabilities
• Establish enterprise standards for MLOps and LLMOps, including CI/CD, model lifecycle management, observability, evaluation, governance, security, and automated deployment
• Design cloud-native AI infrastructure using Kubernetes, containers, infrastructure as code, microservices, and event-driven architectures
• Ensure the AI platform delivers high availability, scalability, resilience, performance, and cost optimization for enterprise workloads
• Partner with AI Engineers and Data Scientists to productionize AI and Generative AI solutions
• Collaborate with Security, Risk, and Compliance teams to implement Responsible AI, governance, access controls, auditability, and regulatory requirements
• Drive platform reliability through monitoring, incident management, capacity planning, disaster recovery, and operational excellence
• Evaluate emerging AI technologies and integrate new platform capabilities that improve developer productivity and enterprise AI adoption
• Foster engineering excellence by promoting software engineering best practices, automation, documentation, and continuous improvement across the AI engineering organization

Skills

Python

Kubernetes

Docker

APIs

Microservices

Infrastructure as Code

Cloud platforms

Leadership

Mentoring

Communication

Education

Bachelor's or Master's in Computer Science / Software Engineering / AI

Tools

AWS

Azure

Google Cloud Platform

Job description

Mastercard seeks a Lead AI Platform Engineer to guide the design, development, and evolution of its enterprise AI platform, enabling teams to build, deploy, and operate AI and Generative AI solutions at scale.

You will manage AI engineers, define roadmaps, and partner across Architecture, Cloud, Data, Security, Product, and Data Science to deliver secure, scalable AI services enterprise-wide.