Architect, build, and operate a secure, scalable foundation model API platform. Define API standards, security and governance controls, ensure reliability, observability, cost control, and partner with AI/ML and platform teams to productionize model capabilities. Lead design/code reviews and mentor engineers to maintain high engineering and operational standards.
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 Software Engineer
Overview
Mastercard is seeking a Principal Software Engineer to architect, build, and operate the API platform that securely exposes foundation model capabilities across the organization. This role is critical to enabling safe, scalable, and compliant adoption of generative AI and advanced analytics across Mastercard products and services.
As a senior technical authority, you will define the architectural standards and operational practices that allow teams to consume AI model capabilities reliably and responsibly. You will partner closely with AI/ML engineers, product, security, and platform teams to deliver production-grade APIs that meet Mastercard's requirements for performance, resilience, governance, and trust.
Role
In this role, you will be responsible for end-to-end ownership of the foundation model API layer, ensuring it is secure, scalable, observable, and easy to adopt.
Key responsibilities include:
Architect and build enterprise-grade API platforms that expose foundation model capabilities (e.g. inference, embeddings, agents) to internal consumers
Define and enforce API standards, including versioning, backward compatibility, SDKs, and developer experience best practices
Design and implement security and governance controls, including authentication, authorization, policy enforcement, audit logging, and usage limits
Ensure platform reliability, scalability, and performance, including traffic management, caching, retries, and graceful degradation
Partner with AI/ML engineering teams to productionize model capabilities while abstracting complexity from downstream consumers
Drive observability and cost control, delivering usage metrics, monitoring, alerting, and cost attribution across tenants and applications
Lead technical design reviews and code reviews for critical services, setting a high bar for engineering quality and operational readiness
Influence broader platform and AI strategy through architectural guidance, technical proposals, and trade-off analysis
Mentor senior engineers and act as a role model for secure, resilient, and maintainable software engineering practices
All About You
Extensive experience designing and operating large-scale, distributed production systems
Deep expertise in API and platform engineering, including REST and/or gRPC, service gateways, and multi-tenant architectures
Strong background in software security, including authN/authZ, encryption, secrets management, and threat modeling
Experience building services in cloud-native environments (e.g. Kubernetes, managed cloud services on AWS, Azure, or GCP)
Proven ability to deliver reliable, observable, and cost-efficient services in high-availability environments
Strong programming skills in one or more backend languages (e.g. Java, Go, C#, Kotlin, Python)
Familiarity with foundation model integration patterns, such as inference APIs, embeddings, RAG pipelines, and safety controls (preferred)
Experience working in regulated or enterprise environments, with an understanding of compliance, auditability, and risk management
Excellent communication skills with the ability to influence technical direction across teams
Demonstrated leadership through technical excellence, mentorship, and architectural ownership, rather than people management alone
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:
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 Software Engineer
Overview
Mastercard is seeking a Principal Software Engineer to architect, build, and operate the API platform that securely exposes foundation model capabilities across the organization. This role is critical to enabling safe, scalable, and compliant adoption of generative AI and advanced analytics across Mastercard products and services.
As a senior technical authority, you will define the architectural standards and operational practices that allow teams to consume AI model capabilities reliably and responsibly. You will partner closely with AI/ML engineers, product, security, and platform teams to deliver production-grade APIs that meet Mastercard's requirements for performance, resilience, governance, and trust.
Role
In this role, you will be responsible for end-to-end ownership of the foundation model API layer, ensuring it is secure, scalable, observable, and easy to adopt.
Key responsibilities include:
Architect and build enterprise-grade API platforms that expose foundation model capabilities (e.g. inference, embeddings, agents) to internal consumers
Define and enforce API standards, including versioning, backward compatibility, SDKs, and developer experience best practices
Design and implement security and governance controls, including authentication, authorization, policy enforcement, audit logging, and usage limits
Ensure platform reliability, scalability, and performance, including traffic management, caching, retries, and graceful degradation
Partner with AI/ML engineering teams to productionize model capabilities while abstracting complexity from downstream consumers
Drive observability and cost control, delivering usage metrics, monitoring, alerting, and cost attribution across tenants and applications
Lead technical design reviews and code reviews for critical services, setting a high bar for engineering quality and operational readiness
Influence broader platform and AI strategy through architectural guidance, technical proposals, and trade-off analysis
Mentor senior engineers and act as a role model for secure, resilient, and maintainable software engineering practices
All About You
Extensive experience designing and operating large-scale, distributed production systems
Deep expertise in API and platform engineering, including REST and/or gRPC, service gateways, and multi-tenant architectures
Strong background in software security, including authN/authZ, encryption, secrets management, and threat modeling
Experience building services in cloud-native environments (e.g. Kubernetes, managed cloud services on AWS, Azure, or GCP)
Proven ability to deliver reliable, observable, and cost-efficient services in high-availability environments
Strong programming skills in one or more backend languages (e.g. Java, Go, C#, Kotlin, Python)
Familiarity with foundation model integration patterns, such as inference APIs, embeddings, RAG pipelines, and safety controls (preferred)
Experience working in regulated or enterprise environments, with an understanding of compliance, auditability, and risk management
Excellent communication skills with the ability to influence technical direction across teams
Demonstrated leadership through technical excellence, mentorship, and architectural ownership, rather than people management alone
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.
Mastercard Dublin, Dublin, IRL Office



One South County, South County Business Park, Dublin, Dublin, Ireland, D18
Similar Jobs at Mastercard
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Lead architecture and technical strategy for a global virtual card platform. Design and deliver scalable, secure, highly-available services, mentor teams, collaborate with product and enterprise functions, and drive engineering excellence and continuous improvement.
Top Skills:
Application Lifecycle Management (Alm) ToolsContainer Orchestration (Kubernetes)ContainersCryptographyDomain Driven Design (Ddd)Functional ProgrammingJavaMessaging TechnologiesPersistence TechnologiesPkiPublic CloudSpring FrameworkTesting Methodologies And Tools
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Design and build production-grade, AI-enabled and agentic applications and platform capabilities. Apply agent orchestration, prompt/context management, and AI tooling to improve developer productivity. Build cloud-native services with reliability, observability, security, and CI/CD. Partner with product, data science, and engineering to move prototypes to production and drive platform-level engineering improvements.
Top Skills:
Agentic Development PatternsAi Coding AssistantsAi FrameworksAi SdksAPIsAutomated TestingAWSAzureCi/CdData PipelinesDistributed SystemsEmbeddingsEvent-Driven ArchitecturesGenerative AiInference ApisJavaKubernetesNext.JsPythonReactRetrieval-Augmented Generation
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Lead hands-on design and delivery of production AI/agentic applications and cloud-native services. Define engineering patterns for reliability, security, observability, and governance. Drive end-to-end delivery, mentor engineers, collaborate with Applied AI, Product, Security, and Platform teams, and shape technical roadmaps to scale AI-enabled products.
Top Skills:
AWSAzureCi/CdDevsecopsGCPJavaKubernetesLlmsNext.JsPythonReact
What you need to know about the Dublin Tech Scene
From Bono and Oscar Wilde to today's tech leaders, Dublin has always attracted trailblazers, with more than 70,000 people working in the city's expanding digital sector. Continuing its legacy of drawing pioneers, the city is advancing rapidly. Ireland is now ranked as one of the top tech clusters in the region and the number one destination for digital companies, with the highest hiring intention of any region across all sectors.




