Lead DevOps Engineer – AI & Data (Foundation Models)

{ "jobLocation" : { "@type" : "Place", "address" : { "@type" : "PostalAddress", "addressCountry" : "Ireland", "addressLocality" : "Dublin, Ireland" } }, "hiringOrganization" : { "name" : "Ireland: Mastercard Ireland Limited", "@type" : "Organization", "sameAs" : "" }, "identifier" : { "name" : "Lead DevOps Engineer – AI & Data (Foundation Models)", "@type" : "PropertyValue", "value" : "R-286222" }, "datePosted" : "2026-07-21", "validThrough" : "2026-07-28", "employmentType" : "FULL_TIME", "title" : "Lead DevOps Engineer – AI & Data (Foundation Models)", "description" : "Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Lead DevOps Engineer – AI & Data (Foundation Models) Overview Mastercard is seeking a DevOps Engineer to support a strategic AI engineering team focused on foundation model development and AI use case delivery. This role is responsible for enabling reliable, scalable, and automated deployment of AI systems—ensuring models and supporting services can move efficiently from development to production. You will work closely with AI engineers, data engineers, and software engineers to build and maintain the CI/CD pipelines, cloud infrastructure, and runtime environments required to support production AI workloads. This role is critical in ensuring that AI solutions are delivered with strong standards for reliability, security, and operational excellence. Role In this role, you will be responsible for building and operating the infrastructure and deployment pipelines that enable AI systems at scale. Key responsibilities include: Design and maintain CI/CD pipelines for AI and data workloads, supporting model training, testing, and deployment Automate build, deployment, and release processes across environments, ensuring consistency and reliability Manage and optimise cloud infrastructure (primarily AWS, with flexibility across cloud platforms) to support AI and data workloads Support deployment and operation of AI models, including inference services, batch jobs, and data pipelines Collaborate with data and AI engineers to streamline development-to-production workflows, reducing friction and cycle time Implement monitoring, logging, and alerting to ensure system observability and rapid issue resolution Ensure systems are designed for high availability, resilience, and performance Embed security best practices into deployment pipelines, including secrets management, access control, and secure configuration Support Databricks environments and workflows where applicable, including job orchestration and integration with data pipelines Contribute to troubleshooting production issues and participating in incident response and post‑incident improvements Promote DevOps best practices, including infrastructure as code, automation, and continuous improvement All About You 5-8 years of experience in a DevOps, platform engineering, or similar role supporting production systems Strong experience building and maintaining CI/CD pipelines in production environments Hands‑on experience with cloud platforms, particularly AWS (experience with Azure or GCP also valuable) Experience with infrastructure as code tools (e.g. Terraform, CloudFormation, or similar) Familiarity with containerisation and orchestration (e.g. Docker, Kubernetes) Experience supporting data and AI workloads, including model deployment pipelines, batch processing, or streaming jobs Working knowledge of monitoring and observability tools (e.g. logging, metrics,