Lead AI engineer

Job Description

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 Lead 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 Lead AI Engineering Engineer to drive hands‑on 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 emphasis on building production‑grade AI systems. This is a senior individual contributor and technical leadership role. You will lead by example through deep hands‑on engineering, influence technical direction, and partner closely with Applied AI, Data Science, and Product teams to take AI solutions from experimentation to secure, scalable production. Role • Lead hands‑on development of AI and agentic systems from design through production deployment • Build and operate ML/AI services, pipelines, and APIs using strong software engineering practices • Design and implement ML engineering capabilities such as model serving, monitoring, evaluation, and retraining • Partner with data scientists to productionise models and experiments efficiently • Contribute directly to data preparation, feature engineering, experimentation, and modelling when required • Drive technical design reviews and provide mentorship to engineers and data scientists • Ensure AI solutions meet Mastercard standards for performance, reliability, security, and governance • Collaborate closely with platform, security, and infrastructure teams to ship responsibly at scale All about you • Strong experience as a hands‑on AI engineer, ML engineer, or senior software engineer working on production AI systems • Solid foundations in software engineering, system design, and distributed systems • Proven experience productionising machine learning models and operating them at scale •

Required Skills