Principal, Software Engineering

Mastercard is hiring a Principal, Software Engineering in Dublin, Ireland. Level rates it ; you can apply on Level.

AI in this role

claudecopilotdatabricks

ai-agents

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 Engineering

Who is Mastercard?
Mastercard is a global technology company in the payments industry, building digital platforms that securely power commerce at global scale. Our technology enables innovation across financial services, data, AI, and digital experiences, while maintaining the highest standards of reliability, security, and trust.
Business & Market Insights (B&MI) is Mastercard’s data, analytics, and intelligence organization, responsible for transforming vast, global data assets into actionable insights and decision support products for customers across industries. B&MI builds platforms and products that move beyond static analytics, embedding AI, advanced modeling, and increasingly agentic systems directly into customer workflows to help clients understand what is happening, what will happen next, and what actions to take. The team operates on a global scale, where product, engineering, and data teams come together to deliver secure, governed, and production ready intelligence solutions that drive measurable business outcomes.
Role Summary
We are looking for a Principal Engineer within our Advisors & Transformation group who will be responsible for accelerating our consulting transformation through AI & technology, partnering closely with business, product, AI, data, and engineering leaders to establish unified technology for the future of Consulting. This Principal Engineer will design both a scalable and reusable AI Platform that will manage and drive AI productivity across the consulting organization, support AI commercialization in consulting engagements, and support existing portfolio or technology partnerships.
The Principal Engineer will help scale tooling such as Claude, Copilot, and Cowork; enable agent orchestration and integration layers; extend AI knowledgebase capabilities; establish finops/tokenops models; and distribute reusable AI best practices, skills, and agents across Consulting.
This is a highly collaborative role that will require close partnership with enterprise and services teams including enterprise AI, data governance, corporate security, compliance, sourcing, and Consulting business leaders. Success will require building shared capabilities into scalable, day-to-day productivity and commercialization solutions supporting thousands of advisors and consultants.

Roles and Responsibilities
• As a Principal Software Engineer, you will:
• Design and build a scalable, reusable AI Platform for the program
• Help drive AI enablement across the wider group.
• Lead technical design and architecture, ensuring scalability, security, and performance.
• Support ongoing initiatives and lead technical design and drive solutions and implementation with key stakeholders.
• Drive migration efforts for key components toward the future state architecture.
• Help define and implement a strategy towards future state architecture.
• Collaborate with cross-functional teams to deliver innovative AI solutions that enhance user experience and accelerate digital transformation.
• Help ensure solutions align with Mastercard technology standards, architecture expectations, operating requirements, security, reliability, and scale needs.
• Mentor engineering teams and establish best practices
• Serve as the architecture advisor for new business opportunities, ensuring technical feasibility, capability needs, and architecture implications are considered early in the opportunity lifecycle.
• Partner with product, business, sourcing, and engineering teams to shape opportunity hypotheses, solution concepts, business cases, and early feasibility assessments.
o Evaluate new ideas, market signals, emerging technology trends, and opportunity spaces through technology, architecture, and capability lens.
o Support the design and evolution of agentic and AI-enabled opportunity identification capabilities, taxonomies, prompt architectures, agent workflows, evaluation frameworks, and supporting intelligence systems as relevant to the role.
• Challenge assumptions and identify material technical risks early, before significant resources are committed to development or deployment.
• Guide architecture, platform, and capability decisions during incubation, prototype, market test, commercialization, and scale phases.
• Identify common capabilities, platforms, architectural patterns, and reusable assets that can accelerate value creation across multiple opportunities.
o Define and maintain perspectives on relevant target-state architectures, including how future capabilities should be structured, integrated, governed, and scaled.
o Help ensure solutions align with Mastercard technology standards, architecture expectations, operating requirements, security, reliability, and scale needs.
o Mentor and influence engineers, architects, and product partners by contributing to shared engineering standards, architectural decisions, and technical decision quality.

Required Skills and Experience
We are seeking a dynamic and experienced Principal Engineer who is passionate about AI, engineering, transformation, and scaled business impact
• Bachelor’s degree in computer science, Engineering, or equivalent practical experience.
• Significant professional experience building distributed, production-grade software systems, including 8 or more years of full-stack engineering experience in an agile production environment.
• Experience executing a technology strategy for a market-facing business in close collaboration with Product, Data Science, business, and peer technology leaders.
• Strong understanding of GenAI, agentic workflows, AI enablement, orchestration patterns, reusable agent/skill libraries, and applied AI delivery in a scaled enterprise environment.
• Experience scaling productivity capabilities across a large team, including commercial AI and agentic platforms.
• Strong understanding of APIs, services, asynchronous workflows, distributed systems, and enterprise-grade software architecture.
• Experience building or integrating systems that use LLMs, AI services, agent frameworks, workflow engines, orchestration platforms, or related technologies.
• Experience building, integrating, and scaling platforms or internal products that improve productivity, standardization, and delivery quality across large user populations.
• A strong hands-on technologist with very strong Object-Oriented Design and excellent programming skills, design principles aimed at creating re-usable, scalable components
• Passionate about AI, emerging technologies and trends.
• Familiarity with cloud technologies and platforms, including but not limited to AWS EMR, Aurora, Databricks, and Snowflake, used to build and scale data-intensive applications.
• Ability to analyse, conceptualize and create cutting edge technical solutions based on the business needs
• Strong communication skills, written and verbal, with experience presenting to executive and cross-functional stakeholders.
• Coordination and organization skills and the ability to work with multiple stakeholders and vendors across locations to ensure success of the project.
• Strong understanding, inclination, and experience of working in an Agile environment.
• Strong technical judgment and ability to evaluate tradeoffs across build, buy, partner, platform, architecture, scalability, integration, and operating model considerations.

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.

How we rate this

Principal, Software Engineering at Mastercard rates 64 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Principal, Software Engineering is an open job at Mastercard.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Dublin, Ireland.
The job was posted on October 9, 2026.
Seniority: lead.
Applications are handled by Mastercard. Apply on Mastercard

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI agentsClaudeCopilotDatabricks

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Walk me through how you've used Claude in your day-to-day work.
What are the limits of Copilot that you've run into, and how did you work around them?
What's a project where you used Databricks hands-on?
Describe a typical day in a role like this one: which parts run through AI directly?

Adapt your resume

List these exact terms on your resume: AI agents, Claude, Copilot, and Databricks. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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