Develop AI and big data solutions for real-time fraud and cyber-threat detection. Responsibilities include building data pipelines and feature engineering workflows, processing large-scale datasets, improving model monitoring and drift detection, applying MLOps and automation, and deploying scalable AI capabilities. The role collaborates with data scientists, engineers, and product teams to improve model performance, reliability, and operational efficiency.
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, Big Data & AI Solutions
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 realize 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 Security Solutions Data Science team develops AI and machine learning capabilities that help protect the global payments ecosystem from fraud and cyber threats. Supporting Mastercard's Safety Net product, the team creates and enhances models that analyze billions of transactions and identify suspicious activity in real time.
As a Senior AI Engineer, you will work at the intersection of AI engineering and big data engineering, helping improve the models, data assets, and operational processes that power fraud detection. You will collaborate closely with Data Scientists and Engineers to strengthen feature engineering, advance model monitoring capabilities, and deliver AI-driven solutions that improve performance and efficiency.
Role
As a Senior AI Engineer, you will: • Support machine learning models that help detect cyber-attacks, fraud and improve decision intelligence. • Create data pipelines and feature engineering workflows that enable model development and evaluation. • Process and analyze large-scale datasets to uncover insights and improve model inputs. • Strengthen monitoring, observability, and drift detection capabilities across production environments. • Apply automation and MLOps practices to improve reliability, efficiency, and scalability. • Develop AI-powered solutions that address engineering challenges and streamline operational processes.
-Partner with Data Scientists, Engineers, and Product teams to bring new capabilities into production. • Contribute ideas that improve model performance, operational visibility, and team productivity.
Required Qualifications • Master's degree with relevant experience, or Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field; equivalent practical experience will also be considered. • Proficiency in Python, PySpark, SQL, and distributed data processing. • Hands-on experience with feature engineering, large-scale data processing, and analytics. • Hands-on experience with Databricks, Airflow, Hadoop, Linux/Unix, cloud-native technologies • Understanding of machine learning and deep learning techniques. • Understanding of model deployment, evaluation, monitoring, and optimization. • Knowledge of MLOps concepts including testing, automation, CI/CD, and version control. • Ability to communicate technical concepts and collaborate across teams.
Preferred Qualifications • Fraud, cybersecurity, payments, or risk management domains. • Experience with Generative AI, LLMs, RAG, or agentic AI applications. • Familiar with AI-assisted development tools such as GitHub Copilot, or Claude Code. • Experience working with cloud-based data and AI environments.
Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact [email protected] and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.
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:
In line with Mastercard's total compensation philosophy and assuming that the job will be performed in Canada, the successful candidate will be offered a competitive pay based on location, experience and other qualifications for the role and may be eligible to participate in a discretionary annual incentive program.
Pay Ranges
Vancouver, Canada: $111,000 - $160,000 CAD
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, Big Data & AI Solutions
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 realize 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 Security Solutions Data Science team develops AI and machine learning capabilities that help protect the global payments ecosystem from fraud and cyber threats. Supporting Mastercard's Safety Net product, the team creates and enhances models that analyze billions of transactions and identify suspicious activity in real time.
As a Senior AI Engineer, you will work at the intersection of AI engineering and big data engineering, helping improve the models, data assets, and operational processes that power fraud detection. You will collaborate closely with Data Scientists and Engineers to strengthen feature engineering, advance model monitoring capabilities, and deliver AI-driven solutions that improve performance and efficiency.
Role
As a Senior AI Engineer, you will: • Support machine learning models that help detect cyber-attacks, fraud and improve decision intelligence. • Create data pipelines and feature engineering workflows that enable model development and evaluation. • Process and analyze large-scale datasets to uncover insights and improve model inputs. • Strengthen monitoring, observability, and drift detection capabilities across production environments. • Apply automation and MLOps practices to improve reliability, efficiency, and scalability. • Develop AI-powered solutions that address engineering challenges and streamline operational processes.
-Partner with Data Scientists, Engineers, and Product teams to bring new capabilities into production. • Contribute ideas that improve model performance, operational visibility, and team productivity.
Required Qualifications • Master's degree with relevant experience, or Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field; equivalent practical experience will also be considered. • Proficiency in Python, PySpark, SQL, and distributed data processing. • Hands-on experience with feature engineering, large-scale data processing, and analytics. • Hands-on experience with Databricks, Airflow, Hadoop, Linux/Unix, cloud-native technologies • Understanding of machine learning and deep learning techniques. • Understanding of model deployment, evaluation, monitoring, and optimization. • Knowledge of MLOps concepts including testing, automation, CI/CD, and version control. • Ability to communicate technical concepts and collaborate across teams.
Preferred Qualifications • Fraud, cybersecurity, payments, or risk management domains. • Experience with Generative AI, LLMs, RAG, or agentic AI applications. • Familiar with AI-assisted development tools such as GitHub Copilot, or Claude Code. • Experience working with cloud-based data and AI environments.
Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact [email protected] and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.
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.
In line with Mastercard's total compensation philosophy and assuming that the job will be performed in Canada, the successful candidate will be offered a competitive pay based on location, experience and other qualifications for the role and may be eligible to participate in a discretionary annual incentive program.
Pay Ranges
Vancouver, Canada: $111,000 - $160,000 CAD
Mastercard Seattle, Washington, USA Office
Mastercard Seattle, WA Office
1301 5th Ave, Seattle, WA, United States, 98101
Similar Jobs at Mastercard
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Develop Java application logic for Mastercard’s real-time Decision Management platform. Build unit, integration, and functional tests; create scalable, secure, maintainable code; participate in Scrum ceremonies; diagnose complex problems; support sprint commitments; collaborate with stakeholders; and mentor junior engineers. The role involves high-performance applications, streaming analytics, fraud prevention, APIs, and data technologies.
Top Skills:
EasymockIbm Ilog/OdmJavaJunitMockitoOraclePivotal Gemfire GridSpringSQL
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Develop and maintain high-performance Java backend applications for Mastercard’s decision management platform. Responsibilities include software design, coding, unit and integration testing, troubleshooting, feature ownership, Agile/Scrum participation, stakeholder collaboration, and mentoring junior engineers. The role involves building scalable, secure, real-time systems supporting fraud prevention and using technologies such as Spring, Oracle, Docker, Kubernetes, and AI-assisted development tools.
Top Skills:
AngularClaude CodeDockerEasymockGithub CopilotIbm Ilog/OdmJavaJunitKubernetesMockitoOraclePivotal GemfireRest AssuredSeleniumSpringSQL
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Design, develop, test, and maintain high-performance Java applications for Mastercard’s Decision Management platform. Build scalable, secure functionality; create unit, integration, and functional tests; troubleshoot complex issues; and deliver features through Agile/Scrum processes. Collaborate with engineers and stakeholders, mentor junior team members, and communicate risks and progress. The role supports real-time decisioning and fraud prevention using streaming analytics, AI engines, APIs, and distributed technologies.
Top Skills:
AngularClaude CodeDockerEasymockGithub CopilotIbm Ilog/OdmJavaJunitKubernetesMockitoOraclePivotal GemfireRest AssuredSeleniumSpringSQL
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

