Senior AI Engineer, Big Data & AI Solutions

Description

The company is a global technology firm in payments, operating in more than 200 countries and territories. Its goal is an inclusive digital economy that is safe, simple, smart and accessible for everyone.

The Security Solutions Data Science team builds AI and machine learning tools that guard the global payments network against fraud and cyber threats. The team supports the Safety Net product, creating and improving models that scan billions of transactions and flag suspicious activity in real time.

This role sits where AI engineering meets big data engineering. You will help improve the models, data assets and operational processes behind fraud detection, working with Data Scientists and Engineers on feature engineering, model monitoring and AI-driven solutions that raise performance and efficiency.

Responsibilities

• Support machine learning models that detect cyber-attacks and fraud and improve decision intelligence.
• Build data pipelines and feature engineering workflows that make model development and evaluation possible.
• Process and analyze large datasets to find insights and improve model inputs.
• Strengthen monitoring, observability and drift detection in production.
• Apply automation and MLOps practices to make systems more reliable, efficient and scalable.
• Build AI-powered tools that solve engineering problems and streamline operations.
• Work with Data Scientists, Engineers and Product teams to move new capabilities into production.
• Suggest ideas that improve model performance, operational visibility and team productivity.

Requirements

• A Master's degree with relevant experience, or a 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 and 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 explain technical ideas clearly and collaborate across teams.
• Preferred: experience in fraud, cybersecurity, payments or risk management.
• Preferred: experience with Generative AI, LLMs, RAG or agentic AI applications.
• Preferred: familiarity with AI-assisted development tools such as GitHub Copilot or Claude Code.
• Preferred: experience working with cloud-based data and AI environments.
• All activities involving access to company assets, information and networks carry inherent risk, so everyone working for or on behalf of the company is responsible for information security. You must follow the company's security policies and practices, protect the confidentiality and integrity of information you access, report any suspected breach or violation, and complete all periodic mandatory security training.

Conditions

Location: Vancouver, Canada.

Pay range: $111,000 to $160,000 CAD. Actual pay depends on location, experience and other qualifications.

Eligible for a discretionary annual incentive program.

The company is an equal opportunity employer and hires the most qualified candidate for each role without regard to protected characteristics. Accommodation requests for the application or hiring process in the US or Canada go to the company's site.

Benefits

• Eligibility for a discretionary annual incentive program.