Mastercard

3 days ago

Lead DevOps Engineer – AI & Data (Foundation Models)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 20 hours agoStatus: Live

Job Summary

Enable reliable, scalable deployment of AI foundation models by building and operating CI/CD pipelines, runtime environments, and cloud infrastructure. Collaborate with AI, data, and software engineers to streamline development-to-production workflows, automate build/release processes, and ensure observability, resilience, and performance. Embed security best practices into pipelines (secrets, access control, secure configuration) and support production incident response, including Databricks workflows where applicable.

Location: Dublin

Workplace: Onsite

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Sr. Manager level

Key Responsibilities

•Design and maintain CI/CD pipelines for AI and data workloads, including model training, testing, and deployment
•Automate build, deployment, and release processes across environments to ensure consistency and reliability
•Manage and optimize cloud infrastructure (primarily AWS) to support AI and data workloads
•Support deployment and operation of AI models, including inference services, batch jobs, and data pipelines
•Implement monitoring, logging, and alerting for observability; embed security best practices and participate in incident response

Key Requirements

•5-8 years of experience in DevOps, platform engineering, or a similar role supporting production systems
•Strong experience building and maintaining CI/CD pipelines in production environments
•Hands-on experience with cloud platforms, particularly AWS (Azure/GCP also valuable)
•Experience with infrastructure as code tools such as Terraform or CloudFormation
•Familiarity with containerization and orchestration (Docker, Kubernetes) and monitoring/observability tools

Experience:5-8 yearsAI engineeringData platformsProduction systems

Skills:Problem-solvingCollaborationOperational excellenceCommunicationCross-functional teamwork

Tech Stack:AWSAzureGCPTerraformCloudFormationDockerKubernetesDatabricksCI/CDInference servicesBatch processingStreaming jobsLoggingMetricsTracingInfrastructure as codeSecrets managementIAM

Company Brief

Mastercard

Mastercard is a global payments and technology company that processes transactions, provides fraud prevention and data services, and builds payment infrastructure for consumers, businesses, merchants and governments across 200+ countries.

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Purchase, New York, United States

Founded: 1966

Glassdoor: 4.1

Website LinkedIn Glassdoor

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Mastercard

3 days ago

Lead DevOps Engineer – AI & Data (Foundation Models)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 20 hours agoStatus: Live

Job Summary

Location: Dublin

Workplace: Onsite

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Sr. Manager level

Key Responsibilities

•Design and maintain CI/CD pipelines for AI and data workloads, including model training, testing, and deployment
•Automate build, deployment, and release processes across environments to ensure consistency and reliability
•Manage and optimize cloud infrastructure (primarily AWS) to support AI and data workloads
•Support deployment and operation of AI models, including inference services, batch jobs, and data pipelines
•Implement monitoring, logging, and alerting for observability; embed security best practices and participate in incident response

Key Requirements

•5-8 years of experience in DevOps, platform engineering, or a similar role supporting production systems
•Strong experience building and maintaining CI/CD pipelines in production environments
•Hands-on experience with cloud platforms, particularly AWS (Azure/GCP also valuable)
•Experience with infrastructure as code tools such as Terraform or CloudFormation
•Familiarity with containerization and orchestration (Docker, Kubernetes) and monitoring/observability tools

Experience:5-8 yearsAI engineeringData platformsProduction systems

Skills:Problem-solvingCollaborationOperational excellenceCommunicationCross-functional teamwork

Tech Stack:AWSAzureGCPTerraformCloudFormationDockerKubernetesDatabricksCI/CDInference servicesBatch processingStreaming jobsLoggingMetricsTracingInfrastructure as codeSecrets managementIAM

Company Brief

Mastercard

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Purchase, New York, United States

Founded: 1966

Glassdoor: 4.1

Website LinkedIn Glassdoor