Senior AI Engineer, Big Data & AI Solutions

Mastercard is hiring a Senior AI Engineer, Big Data & AI Solutions in Vancouver, Canada. It pays CAD 111k-CAD 160k a year and Level rates it ; you can apply on Mastercard.

Level's read on this job

Level rates this AI engineer role Builds AI ●●●●: the job is building AI systems.
The posting mentions Claude, Copilot and Databricks among its tools and skills.
Level classes it as a senior role.
Mastercard has 1,100+ other open roles on Level.
Posted in the last few days.

AI in this role

claudecopilotdatabricksclaude-code

ragml-ops

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 reasonable_accommodation@mastercard.com 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

How we rate this

Senior AI Engineer, Big Data & AI Solutions at Mastercard rates 89 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● 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. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior AI Engineer, Big Data & AI Solutions is an open job at Mastercard.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is CAD 111k-CAD 160k a year.
The role is based in Vancouver, Canada.
The job was posted on October 27, 2026.
Seniority: senior.
Applications are handled by Mastercard. Apply on Mastercard

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGML OpsClaudeCopilotDatabricksClaude Code

Also common in AI engineer jobs at this level

AI agents AWS Azure Google Cloud PyTorch Java

Pay

Typical AI engineer job: $186k

Use the typical AI engineer figure as a reference when pay comes up. See AI engineer jobs

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you monitor a model once it's live, and how do you know it needs retraining?
What are the limits of Claude that you've run into, and how did you work around them?
What's a project where you used Copilot hands-on?
Walk me through how you've used Databricks in your day-to-day work.

Adapt your resume

List these exact terms on your resume: RAG, ML Ops, 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.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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