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
Senior AI Engineer
Who is Mastercard?
Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realise their greatest potential.
Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.
Overview
The CNPF Data & AI organisation is looking for a Senior AI Engineer to contribute hands-on to the delivery of applied AI and agentic capabilities across our platforms. This role sits at the intersection of software engineering, machine learning engineering, and applied data science, with a strong focus on building and operating production-grade AI systems. This is a senior individual contributor role. You will work closely with Applied AI, Data Science, and Product teams to help take AI solutions from experimentation through to secure, scalable production - bringing strong engineering rigour and a collaborative mindset to everything you build.
Role
Develop and contribute to AI and agentic systems across the full lifecycle from design through production deployment
Build and operate ML/AI services, pipelines and APIs using strong software engineering practices
Implement ML engineering capabilities including model serving, monitoring, evaluation and retraining
Partner with data scientists to productionise models and experiments efficiently
Contribute to data preparation, feature engineering, experimentation and modelling as needed
Participate in technical design reviews and support knowledge sharing across engineering and data science teams
Ensure AI solutions meet Mastercard standards for performance, reliability, security and governance
Collaborate with platform, security, and infrastructure teams to ship responsibly at scale
All about you
Solid experience as a hands-on AI engineer, ML engineer, or software engineer working on production AI systems
Strong foundations in software engineering, system design, and distributed systems
Practical experience productionising machine learning models and supporting their operation at scale
Comfortable working across data engineering, ML engineering, and applied data science tasks
Familiarity with large-scale data platforms and modern ML/AI tooling
Good problem-solving skills with the ability to navigate ambiguous requirements
Collaborative and communicative, able to work effectively across functions and disciplines
What Makes You Stand Out
You have contributed to AI or agentic applications running in real production environments
Hands-on experience with agent-based or LLM-powered systems beyond simple POCs
Good instincts for reliability, observability, and failure handling in AI systems
Ability to move between engineering execution and applied modelling depending on what the problem needs
Eagerness to grow technically and contribute positively to the engineering culture around you
Corporate Security Responsibility
Every person working for, or on behalf of, Mastercard is responsible for information security. All activities involving access to Mastercard assets, information, and networks come with an inherent risk to the organisation and therefore it is expected that the successful candidate 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• Complete all mandatory security trainings in accordance with Mastercard's guidelines
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.
Skills Required
- Hands-on experience building production AI/ML systems
- Strong software engineering foundations, system design, and distributed systems experience
- Practical experience productionizing models and operating them at scale (serving, monitoring, retraining)
- Ability to work across data engineering, ML engineering, and applied data science tasks
- Familiarity with large-scale data platforms and modern ML/AI tooling
- Strong problem-solving, collaboration, and communication skills
- Adhere to Mastercard security policies, ensure confidentiality, and complete mandatory security training
- Experience with agent-based or LLM-powered systems in production
- Experience designing for reliability, observability, and failure handling in AI systems
- Ability to switch between engineering execution and applied modelling as needed
Mastercard Compensation & Benefits Highlights
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Retirement Support — Company information highlights a 10% retirement match on U.S. roles, positioned as best‑in‑class and well above typical large‑employer benchmarks. This level of employer contribution materially strengthens long‑term savings.
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Leave & Time Off Breadth — U.S. postings list 25 vacation days, 5 personal days, 10 company holidays, 80 hours of paid sick/safe time, and up to 20 days of bereavement. A minimum of 16 weeks paid new‑parent leave (including adoption and foster) further expands paid time away.
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Parental & Family Support — Benefits include a minimum of 16 weeks paid new‑parent leave and family‑building support such as fertility, adoption, and surrogacy where legally available. Dependent scholarships, counseling, and protection benefits contribute additional family support.
Mastercard Insights
What We Do
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re building a resilient 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.
Why Work With Us
We live the Mastercard Way: creating value in the communities we touch, growing together through the opportunities we see, and moving fast to innovate and scale. Our collaborative culture and our passionate people are the key to what we do, driving meaningful change as one team and connecting everyone to priceless possibilities.
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Employees engage in a combination of remote and on-site work.
In our ongoing workplace evolution, we’ve introduced hybrid work, Work-From-Elsewhere Weeks and Meeting-Free Days.
















