Build, deploy, and operate production-grade AI and agentic systems. Implement model serving, monitoring, evaluation and retraining. Partner with data scientists to productionize models, contribute to data preparation and feature engineering, and ensure solutions meet performance, security and governance standards while collaborating across platform and infrastructure teams.
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
Senior AI Engineer-1
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:
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-1
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.
Mastercard Seattle, Washington, USA Office
1301 5th Ave, Seattle, WA, United States, 98101
Similar Jobs at Mastercard
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Senior individual contributor building and operating production-grade AI and agentic systems. Responsibilities include designing, deploying, and monitoring ML services, pipelines and APIs; productionising models with data scientists; ensuring reliability, security, and governance; and collaborating with platform, security, and infrastructure teams.
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Lead design, build, and operate API platform exposing foundation model capabilities. Deliver secure, scalable APIs and backend services, integrate models with production, implement CI/CD, observability and security controls, troubleshoot production issues, and mentor engineering teams.
Top Skills:
AuthenticationAuthorizationAWSAzureC#CachingCi/CdDevOpsEmbeddingsFoundation ModelsGCPGoGrpcInferenceJavaLoggingMonitoringPythonRest
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Senior individual contributor building and operating production-grade AI and agentic systems. Responsibilities include designing, deploying, and monitoring ML services, pipelines and APIs; productionising models with data scientists; ensuring reliability, security, and governance; and collaborating with platform, security, and infrastructure teams.
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute

