Senior AI Platform Engineer

Mastercard

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
O Fallon, MOAtlanta, GAAustin, TX
Salary
$115,000–$184,000 / yr
Posted
3 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $158k
This role $150k
$86k most similar roles pay here $223k

This role pays less than 65% of similar roles. Most pay $126,912–$188,924 — the shaded band above. At the midpoint, this role pays about $150k versus about $158k for comparable roles.

Based on 240 similar postings.

Employer

About Mastercard

Mastercard is a global technology company in the payments industry, processing transactions between financial institutions and merchants using its extensive network of credit, debit, and prepaid card products. Industry: Payments Technology & Financial Services

Mastercard currently has 116 open roles on FindRole.

Listed pay typically runs $122,000–$207,000 across 104 roles with salary data.

Most-posted roles

View all roles at Mastercard

At a glance

TL;DR · Senior AI Platform Engineer

As a Senior AI Platform Engineer (DevOps), you will join the AI Platform Engineering team to build, operate, and evolve enterprise-grade AI platforms. You will design and implement foundational infrastructure that supports machine learning, generative AI, and advanced analytics workloads across public and private cloud environments. Your daily responsibilities include automating platform capabilities for seamless deployment, managing MLOps lifecycles, and developing observability solutions such as telemetry, logging, and drift detection. To succeed, you must possess expertise in Python, Kubernetes, OpenShift, Docker, and Helm, while utilizing Infrastructure as Code and CI/CD pipelines. You will solve complex problems regarding scalability, reliability, and governance for large-scale distributed systems. The role focuses on creating the underlying tools and infrastructure that enable internal teams to safely develop and scale AI-powered products across the enterprise.

What you'll do

  • Design, build, and operate enterprise AI platforms for machine learning and generative AI workloads.
  • Engineer scalable solutions across public and private cloud environments ensuring security and reliability.
  • Automate platform capabilities to simplify onboarding, deployment, and lifecycle management for AI solutions.
  • Develop infrastructure and tooling for model training, evaluation, deployment, monitoring, and governance.
  • Implement MLOps capabilities to create repeatable and secure AI development workflows.
  • Design and maintain observability solutions including telemetry, logging, alerting, and drift detection.
  • Drive automation through Infrastructure as Code, CI/CD pipelines, and testing initiatives.
  • Participate in troubleshooting, root cause analysis, and incident response for high-availability platforms.

What we're looking for

  • Experience designing, building, and operating cloud-native systems in enterprise environments.
  • 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.
  • Experience supporting generative AI platforms and large language model (LLM) workloads (preferred).
  • Experience implementing model evaluation, finetuning, guardrails, and model governance controls (preferred).
  • Experience with AI serving infrastructure, inference platforms, or GPU-based workloads (preferred).
  • Experience with OpenShift, Kubernetes, Docker, Helm, GitOps, and Infrastructure as Code (preferred).
  • Familiarity with vector databases, retrieval systems, AI gateways, or agentic systems (preferred).

More like this

Similar roles

Senior DevOps Platform Engineer

Humana

Remote (Louisville, KY) +4 3 days ago $106,900$147,000
Azure GCP Kubernetes Terraform CI/CD GitOps JFrog Artifactory Argo CD SonarQube LaunchDarkly Python PowerShell Bash GitHub Actions Harness OpenShift Linux Windows Agile
7+ yrs exp Remote

Senior AI Platform Engineer

Leidos

Adelphi, MD 11 days ago $107,900$195,050
AWS Kubernetes Docker Terraform CloudFormation Python CI/CD Infrastructure as Code MLOps Amazon Bedrock SageMaker DevSecOps RMF Platform One Iron Bank Big Bang FedRAMP IL5
8+ yrs exp

Senior Platform AI Engineer

Nvidia

17 days ago $184,000$287,500
ML Infrastructure Distributed Systems Python C++ Go Kubernetes Celery Sidekiq Temporal Container Runtimes Model Serving SLA Enforcement Observability EDA Toolchains Silicon Design Backend Infrastructure Security Reliability
8+ yrs exp Hybrid

Senior Platform Software Engineer, AI

Oracle

Nashville, TN 28 days ago $92,500$209,500
Python Go Java C++ Kubernetes OCI Machine Learning LLMs PyTorch TensorFlow Hugging Face CI/CD Microservices Distributed Systems Data Pipelines Service Mesh Prompt Engineering
4+ yrs exp

Senior Platform Software Engineer, AI

Oracle

Nashville, TN 28 days ago $92,500$209,500
Python Go Java C++ LLMs Machine Learning PyTorch TensorFlow Hugging Face Kubernetes CI/CD Oracle Cloud Infrastructure Microservices Distributed Systems Data Pipelines Service Mesh Prompt Engineering
4+ yrs exp

Senior Platform Software Engineer, AI

Oracle

Nashville, TN 28 days ago $92,500$209,500
Python Go Java C++ Kubernetes OCI PyTorch TensorFlow Hugging Face Transformers LLMs Generative AI CI/CD Microservices Distributed Systems Data Pipelines Service Mesh
4+ yrs exp