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About the Role

The AI Platform Engineering team is responsible for building, operating, and evolving Mastercard's enterprise AI platforms and capabilities. This role will help design, implement, and operate foundational platforms that support AI and machine learning workloads across the enterprise, working at the intersection of platform engineering, cloud infrastructure, MLOps, and AI operations.

Responsibilities

Design, build, and operate enterprise AI platforms supporting machine learning, generative AI, and advanced analytics workloads.
Engineer scalable solutions across public and private cloud environments, ensuring security, reliability, availability, and performance.
Build and automate platform capabilities that simplify onboarding, deployment, operations, and lifecycle management for AI solutions.
Develop and maintain infrastructure, tooling, and services that support model training, evaluation, deployment, monitoring, and governance.
Implement and enhance MLOps capabilities that enable repeatable, scalable, and secure AI development workflows.
Design and maintain observability solutions, including telemetry, performance monitoring, logging, alerting, operational analytics, and drift detection.
Support production AI platforms and services, proactively identifying opportunities to improve reliability, scalability, efficiency, and customer experience.
Partner with internal engineering teams to understand requirements, enable platform adoption, and accelerate delivery of AI-powered products.
Collaborate with infrastructure, security, architecture, and governance teams to ensure alignment with enterprise standards, controls, and regulatory requirements.
Evaluate emerging AI technologies, platform capabilities, and industry trends to help shape the future direction of Mastercard's AI ecosystem.
Drive automation and engineering best practices through Infrastructure as Code, CI/CD, testing, and operational excellence initiatives.
Participate in troubleshooting, root cause analysis, operational support, and incident response activities to maintain highly available platforms.
Contribute to technical design discussions, architecture reviews, and long-term platform strategy.
Mentor peers and share knowledge across engineering teams while contributing to a culture of continuous improvement.

Requirements

Experience designing, building, and operating cloud-native systems in enterprise environments.
Strong experience working within both public and private cloud environments.
Experience deploying and managing containerized workloads using Kubernetes or OpenShift.
Strong software engineering and automation experience using Python.
Experience implementing CI/CD pipelines and modern DevOps practices.
Experience supporting production AI, machine learning, data platforms, or large-scale distributed systems.
Strong understanding of MLOps principles and machine learning lifecycle management.
Experience implementing monitoring, observability, telemetry, logging, and operational analytics solutions.
Strong troubleshooting, analytical, and problem-solving skills.
Ability to communicate effectively with technical and non-technical stakeholders.
Experience working in highly collaborative, cross-functional engineering environments.
Experience supporting generative AI platforms and large language model (LLM) workloads.
Experience implementing model evaluation, finetuning, guardrails, and model governance controls.
Experience with model observability, drift detection, telemetry monitoring, and operational analytics.
Experience with AI serving infrastructure and inference platforms.
Experience supporting GPU-based workloads and accelerated computing environments.
Experience with OpenShift, Kubernetes, Docker, Helm, GitOps, and Infrastructure as Code practices.
Experience with enterprise-scale platform engineering, developer enablement, and self-service platform capabilities.
Familiarity with vector databases, retrieval systems, AI gateways, agentic systems, or emerging AI platform technologies.
Experience working within regulated environments requires strong security, governance, and compliance controls.

Skills

Python
Kubernetes
OpenShift
CI/CD
DevOps
MLOps
Infrastructure as Code
Docker
Helm
GitOps

Location

O'Fallon, Missouri
Atlanta, Georgia
Austin, Texas

Work Type

Full-time

Experience Level

Senior

Salary/Compensations

O'Fallon, Missouri: $115,000 - $184,000 USD
Atlanta, Georgia: $115,000 - $184,000 USD
Austin, Texas: $115,000 - $184,000 USD

Benefits

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
5 personal days
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

About the Company

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 payment choices, making transactions secure, simple, smart, and accessible.
Our technology and innovation, partnerships, and networks combined to deliver a unique set of products and services that help people, businesses, and governments realize their greatest potential.
Our decency quotient (DQ) drives our culture and everything we do inside and outside our company.
We cultivate an environment where individuals can thrive, collaborate, and contribute to innovations that power the global economy.

Equal Opportunity

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.