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Mastercard
Mastercard

Global payments and technology company

Principal Software Engineer at Mastercard

RoleMachine Learning
LevelPrincipal
LocationDublin, Ireland
WorkOn-site
TypeFull-time
Posted1 day ago
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About the role

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:

  • 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.

Required skills

API Architecture

Platform Engineering

Distributed Systems

Security

Observability

Generative AI

Software Engineering

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About Mastercard

Mastercard

A financial network that processes payments between banks and cardholders

10,001+

Employees

Purchase

Headquarters

$360B

Valuation

Reviews

10 reviews

3.8

10 reviews

Work-life balance

2.8

Compensation

4.1

Culture

4.2

Career

3.4

Management

3.1

72%

Recommend to a friend

Pros

Great team culture and supportive colleagues

Excellent benefits and compensation

Training and development opportunities

Cons

Work-life balance challenges and long hours

High pressure and stress during peak times

Management issues and lack of direction

Salary Ranges

51 data points

L6

L7

L9

Mid/L4

Director

L5

L6 ·

0 reports

$198,500

total per year

Base

-

Stock

-

Bonus

-

$168,725

$228,275

Interview experience

3 interviews

Difficulty

3.3

/ 5

Duration

14-28 weeks

Offer rate

33%

Experience

Positive 33%

Neutral 34%

Negative 33%

Interview process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Behavioral Interview

5

Super Day/Final Round

6

Offer

Common questions

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

System Design

Past Experience