Role Description We are looking for a highly skilled Senior Platform Engineer to design, optimize, and scale infrastructure for GenAI and LLM workloads. This role is ideal for someone with deep hands-on experience in GPU profiling, distributed training, and high-performance compute environments. You’ll play a key role in building out GenAI platform foundations, supporting production-grade deployments, and partnering closely with data science, MLOps, and application teams to bring cutting-edge AI solutions to life. Key Responsibilities - Design and implement scalable infrastructure for LLM and GenAI workloads across multi-GPU environments. - Perform GPU profiling, benchmarking, and performance optimization for distributed training workloads. - Manage and schedule compute-intensive jobs using Slurm-based clusters and OpenShift/Kubernetes environments. - Enable and optimize the NVIDIA GPU stack (CUDA, cuDNN, NCCL, Triton, RAPIDS, etc.). - Collaborate with cross-functional teams to deploy models in research and production environments. - Build and support GenAI pipelines (fine-tuning, RAG, multi-modal inferencing, LLMOps). - Develop reusable infrastructure templates using tools like Terraform and Helm. - Contribute to internal innovation (PoCs, workshops) and support client-facing delivery engagements. Qualifications - Strong experience with Slurm and distributed training environments. - Hands-on expertise with Red Hat OpenShift and/or Kubernetes. - Deep knowledge of the NVIDIA GPU ecosystem (CUDA, cuDNN, NCCL, Nsight, Triton/TensorRT). - Strong foundation in Linux systems, performance tuning, and multi-GPU optimization. - Experience deploying GenAI workloads (LLM fine-tuning, RAG pipelines, multi-modal systems). - Familiarity with Infrastructure-as-Code tools (Terraform, Ansible). - Experience with cloud GPU environments (GCP, Azure, AWS, OCI) and/or on-prem GPU clusters. Other Qualifications (OQs) - Experience with NVIDIA NIMs, DGX systems, or GPU-accelerated containers. - Knowledge of LLMOps frameworks and MLOps integration. - Familiarity with vector databases and retrieval systems for RAG architectures. - Comfortable working in client-facing environments and collaborating with AI solution teams. Healthcare Domain Experience (Nice to Have) - Experience working with FHIR R4, HL7 v2, or SMART on FHIR. - Integration with EHR systems (e.g., Epic). - Understanding of HIPAA compliance and healthcare data privacy. - Exposure to clinical workflows, CDS Hooks, or patient-facing applications. - Experience building clinical decision support systems or healthcare interoperability solutions. Benefits - Make an impact at one of the world’s fastest-growing AI-first digital engineering companies. - Upskill and discover your potential as you solve complex challenges in cutting-edge areas of technology alongside passionate, talented colleagues. - Work where innovation happens - work with disruptive innovators in a research-focused organization with 60+ patents filed across various disciplines. - Stay ahead of the curve, immerse yourself in breakthrough AI, ML, data, and cloud technologies and gain exposure working with Fortune 500 companies. - If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

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 Principal AI Platform Engineer - AI Center of Excellence Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Overview: The AI Center of Excellence is seeking a Principal AI Infrastructure Engineer to build and scale next-generation infrastructure supporting Mastercard's growing AI workloads. This role focuses on enabling high-performance, scalable platforms across compute, storage, networking, and accelerators. The ideal candidate is technically deep, highly motivated, and brings an innovative, builder mindset to power advanced AI capabilities across the organization. About the Role:• Lead AI infrastructure roadmap for Mastercard's on premise private cloud, spanning strategy, design, procurement, delivery, installation, and lifecycle management, in alignment with enterprise AI priorities and governance frameworks.• Act as a product owner for AI infrastructure, translating business and data science needs into scalable, future proof platform capabilities that support both predictive ML and generative/agentic AI workloads at enterprise scale.• Lead RFI and RFP processes for AI infrastructure components, including CPU, GPU, storage, and networking, defining technical and commercial evaluation criteria, reviewing vendor responses, and driving fact based selection decisions in partnership with sourcing and finance teams.• Architect and scale infrastructure capable of training large scale predictive and generative models on petabytes of data, while supporting low latency inference (real time and batch) with thousands of transactions per second (TPS) across global workloads.• Define and champion modern AI infrastructure standards, including high performance storage , high speed networking , and advanced data center requirements such as liquid cooling and power dense rack design.• Partner closely with data science, MLOps, and platform teams to ensure infrastructure choices align with model development, training, deployment, observability, and responsible AI requirements across the AI lifecycle.• Collaborate cross functionally with enterprise architecture, security, risk, governance, compliance, and legal teams to ensure solutions meet Mastercard's regulatory, resiliency, and ethical AI standards.• Influence senior leadership and executive stakeholders, clearly articulating trade offs, ROI, and risk, and confidently advocating for the right technical and architectural decisions through structured narratives and executive level presentations.• Stay ahead of industry trends in AI infrastructure, Generative AI, and Agentic AI, continuously assessing emerging technologies and vendors to inform long term strategy and investment decisions. All About You:• Bachelor's degree in Computer Science, Electronics, or a related engineering field is required.• Background:• Significant professional history of experience in large scale infrastructure, platform engineering, or systems architecture roles within a complex enterprise environment.• Proven experience owning infrastructure roadmaps and driving delivery in on premise or private cloud environments at scale.• AI & Data Foundation:• Good working knowledge of AI/ML concepts, data science workflows, MLOps practices, and model lifecycle management.• Familiarity with Generative AI and Agentic AI architectures, including their unique infrastructure, networking, and latency requirements.• Infrastructure Expertise:• Deep understanding of compute (CPU/GPU), high performance storage, and networking technologies used in modern AI platforms.• Hands on or architectural exposure to high density, high power AI infrastructure, including cooling, power, and data center design considerations.• Product & Vendor Mindset:• Strong product thinking-able to balance user needs, technical feasibility, cost, and long term platform evolution.• Demonstrated experience running RFIs/RFPs, evaluating vendor proposals, and partnering with sourcing and finance teams to make informed investment decisions.• Enterprise Leadership:• Comfortable navigating and influencing within a large, matrixed organization, working effectively with security, governance, architecture, and compliance stakeholders.• Executive ready communicator with the ability to present complex technical topics clearly, persuasively, and credibly to senior leaders.• Personal Attributes:• Strategic, opinionated, and data driven, with the confidence to challenge assumptions and defend well reasoned design decisions.• Curious, forward looking, and passionate about building the AI foundations that enable enterprise scale innovation. #AI1 Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: - Abide by Mastercard's security policies and practices; - Ensure the confidentiality and integrity of the information being accessed; - Report any suspected information security violation or breach, and - Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines. In line with Mastercard's total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations. Pay Ranges Arlington, Virginia: $195,000 - $323,000 USD Purchase, New York: $196,000 - $323,000 USD Remote - Virginia: $170,000 - $281,000 USD Washington, District of Columbia: $196,000 - $323,000 USD Job Posting Window Posting windows may change based on the volume of applications received and business necessity. Candidates are encouraged to apply expeditiously.

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 Principal AI Platform Engineer - AI Center of Excellence Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Overview: The AI Center of Excellence is seeking a Principal AI Infrastructure Engineer to build and scale next-generation infrastructure supporting Mastercard's growing AI workloads. This role focuses on enabling high-performance, scalable platforms across compute, storage, networking, and accelerators. The ideal candidate is technically deep, highly motivated, and brings an innovative, builder mindset to power advanced AI capabilities across the organization. About the Role:• Lead AI infrastructure roadmap for Mastercard's on premise private cloud, spanning strategy, design, procurement, delivery, installation, and lifecycle management, in alignment with enterprise AI priorities and governance frameworks.• Act as a product owner for AI infrastructure, translating business and data science needs into scalable, future proof platform capabilities that support both predictive ML and generative/agentic AI workloads at enterprise scale.• Lead RFI and RFP processes for AI infrastructure components, including CPU, GPU, storage, and networking, defining technical and commercial evaluation criteria, reviewing vendor responses, and driving fact based selection decisions in partnership with sourcing and finance teams.• Architect and scale infrastructure capable of training large scale predictive and generative models on petabytes of data, while supporting low latency inference (real time and batch) with thousands of transactions per second (TPS) across global workloads.• Define and champion modern AI infrastructure standards, including high performance storage , high speed networking , and advanced data center requirements such as liquid cooling and power dense rack design.• Partner closely with data science, MLOps, and platform teams to ensure infrastructure choices align with model development, training, deployment, observability, and responsible AI requirements across the AI lifecycle.• Collaborate cross functionally with enterprise architecture, security, risk, governance, compliance, and legal teams to ensure solutions meet Mastercard's regulatory, resiliency, and ethical AI standards.• Influence senior leadership and executive stakeholders, clearly articulating trade offs, ROI, and risk, and confidently advocating for the right technical and architectural decisions through structured narratives and executive level presentations.• Stay ahead of industry trends in AI infrastructure, Generative AI, and Agentic AI, continuously assessing emerging technologies and vendors to inform long term strategy and investment decisions. All About You:• Bachelor's degree in Computer Science, Electronics, or a related engineering field is required.• Background:• Significant professional history of experience in large scale infrastructure, platform engineering, or systems architecture roles within a complex enterprise environment.• Proven experience owning infrastructure roadmaps and driving delivery in on premise or private cloud environments at scale.• AI & Data Foundation:• Good working knowledge of AI/ML concepts, data science workflows, MLOps practices, and model lifecycle management.• Familiarity with Generative AI and Agentic AI architectures, including their unique infrastructure, networking, and latency requirements.• Infrastructure Expertise:• Deep understanding of compute (CPU/GPU), high performance storage, and networking technologies used in modern AI platforms.• Hands on or architectural exposure to high density, high power AI infrastructure, including cooling, power, and data center design considerations.• Product & Vendor Mindset:• Strong product thinking-able to balance user needs, technical feasibility, cost, and long term platform evolution.• Demonstrated experience running RFIs/RFPs, evaluating vendor proposals, and partnering with sourcing and finance teams to make informed investment decisions.• Enterprise Leadership:• Comfortable navigating and influencing within a large, matrixed organization, working effectively with security, governance, architecture, and compliance stakeholders.• Executive ready communicator with the ability to present complex technical topics clearly, persuasively, and credibly to senior leaders.• Personal Attributes:• Strategic, opinionated, and data driven, with the confidence to challenge assumptions and defend well reasoned design decisions.• Curious, forward looking, and passionate about building the AI foundations that enable enterprise scale innovation. #AI1 Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: - Abide by Mastercard's security policies and practices; - Ensure the confidentiality and integrity of the information being accessed; - Report any suspected information security violation or breach, and - Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines. In line with Mastercard's total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations. Pay Ranges Arlington, Virginia: $195,000 - $323,000 USD Purchase, New York: $196,000 - $323,000 USD Remote - Virginia: $170,000 - $281,000 USD Washington, District of Columbia: $196,000 - $323,000 USD Job Posting Window Posting windows may change based on the volume of applications received and business necessity. Candidates are encouraged to apply expeditiously.

• Develop, enhance, and maintain gateway or platform solutions • Collaborate with cross-functional teams • Ensure compliance with IRS MBI standards • Participate in the architectural design of API gateways.