Senior AI Platform Engineer: Scalable ML Ops & Cloud

Mastercard; Austin (TX); On-site; USD 115,000 - 184,000; Full time

Benefits offered by this job

Health insurance

401k with company match

Paid time off & parental leave

Job summary

Mastercard seeks a Senior AI Platform Engineer (DevOps) to design, build, and operate enterprise AI platforms that support machine learning across public and private clouds.

You will work at the intersection of platform engineering, cloud infrastructure, MLOps, and AI operations to deliver scalable, secure AI capabilities that enable teams to safely develop, deploy, observe, and scale AI solutions enterprise-wide.

Qualifications

• Experience designing, building, and operating cloud-native systems in enterprise environments.
• Strong experience with public and private cloud environments.
• Experience deploying and managing containerized workloads using Kubernetes or OpenShift.
• Strong software engineering and automation using Python.
• Experience implementing CI/CD pipelines and modern DevOps practices.
• Experience supporting production AI, machine learning, data platforms, or large-scale distributed systems.
• Understanding of MLOps principles and ML lifecycle management.
• Experience implementing monitoring, observability, telemetry, logging, and analytics.

Responsibilities

• Design, build, and operate enterprise AI platforms for ML workloads.
• Engineer scalable solutions across public and private clouds with strong security and reliability.
• Automate onboarding, deployment, operations, and lifecycle management for AI solutions.
• Develop and maintain infrastructure, tooling, and services for model training, evaluation, deployment, monitoring, and governance.
• Implement and enhance MLOps for repeatable, scalable AI development workflows.
• Design and maintain observability solutions including telemetry, performance monitoring, logging, and drift detection.
• Support production AI platforms and proactively improve reliability, scalability, and customer experience.
• Partner with internal teams to enable platform adoption and accelerate AI product delivery.
• Collaborate with security, governance, and architecture to meet enterprise standards.

Skills

Cloud-native systems

Kubernetes

OpenShift

Python

CI/CD

MLOps

Observability

Automation

Security best practices

Collaboration

Tools

OpenShift

Kubernetes

Docker

Helm

GitOps

Infrastructure as Code

Job description

Mastercard seeks a Senior AI Platform Engineer (DevOps) to design, build, and operate enterprise AI platforms that support machine learning across public and private clouds.

You will work at the intersection of platform engineering, cloud infrastructure, MLOps, and AI operations to deliver scalable, secure AI capabilities that enable teams to safely develop, deploy, observe, and scale AI solutions enterprise-wide.