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Added 5 mins ago
UO
Undergraduate Program Advising Officer
University of Victoria
Victoria, BC
- Full-time
The Peter B. Gustavson School of Business is well-known as a leader in international education. Our undergraduate programs are designed around the four pillars of the school (international,…
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- Full-time
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RBC

Manager, AML Model Testing

Toronto, ON, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Nov 19, 2026
Posting language: English
Posted: Nov 4, 2026

Original job description

Job Description

What is the opportunity?

In support of RBC’s commitment to maintaining a robust enterprise AML Program, the AML Model Testing Manager will support the ongoing AML model development testing process to ensure the accuracy and reliability of model code through comprehensive testing. This role will be responsible for reviewing model design/update context, conducting code logic/standard validation, designing unit/integration tests, providing actionable insights for improvement, and documenting all findings/recommendations to ensure the model logic correctness, and functionality as per design. In addition to the core responsibilities outlined above, this position will explore and advance the application of emerging AI technologies in AML model testing. The role requires exploring and designing AI Agent workflows to automate portions of testing work, while establishing appropriate quality assurance mechanisms to ensure the accuracy and reliability of testing results in an AI-involved work environment.

What will you do?

Gather relevant test information and model white paper to understand the model’s design background and update context. Communicate with the development team to understand the testing requirements.
Work with Testing Lead to determine the testing priorities based on business requirements, define the testing scope and methodology and develop a testing plan.
Set up the testing environment and develop testing programs to use during testing.
Use the model white paper as a guideline to conduct code logic validation, implementing coding standard checks, compare difference between code and documentation, ensuring the code adheres to best practices and passes an initial logic review.
Design unit tests, covering normal cases, abnormal cases, and corner cases to verify that the code consistently produces correct results that meet business requirements under all circumstances.
Develop integration tests as needed to ensure that different modules, components, or systems function correctly together.
Provide reasons for test failures along with suggestions for improvement based on the testing results.
Collaborate closely with stakeholders to facilitate issue resolution and ensure the model passes all test cases.
Prepare a detailed and well-structured test report documenting the testing methodologies, designed test cases, identified code issues, and corresponding resolutions.
Ensure compliance with regulatory and internal documentation standards.
Evaluate the applicability of existing AI tools in AML model testing
Explore AI Agent workflow implementations to automate routine testing operations, including code logic validation, compliance auditing, and intelligent unit test generation, thereby enhancing testing efficiency and reducing manual workload.
Explore how to define decision boundaries for AI Agents and establish triggers for human review checkpoints.
Collaborate closely with Senior Manager and other stakeholders to align AML testing strategies with business needs.
Stay informed of industry best practices in AML model development testing.
Support process improvements to enhance efficiency and robustness in AML model code testing.

What do you need to succeed?

Must-have

Hands-on experience with SQL, SAS, Python and Dataiku for data processing, querying and automation.
Post-secondary education or equivalent.
Strong analytical, logical, and critical thinking skills with the ability to design complex testcases that covers all scenarios.
Effective communication and collaboration skills to work effectively with cross-functional teams.

Nice-to-have

Bachelor's degree in Statistics, Mathematics, Engineering and Computer Science, or a related field.
Familiarity with machine learning or data science techniques.
Practical experience using AI tools for code testing or software development.

What’s in it for you?

We thrive on the challenge to be our best, thinking progressively to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

A comprehensive Total Rewards Program including bonuses and flexible benefits
Leaders who support your development through coaching and managing opportunities
Ability to make a difference and lasting impact
Work in an agile, collaborative, progressive, and high-performing team
The opportunity to interface with executives from many different parts of the organization

Job Skills

Anti Money Laundering Training, Business Perspective, Communication, Decision Making, Financial Regulation, Interpersonal Relationship Management, Operational Integrity, Organizational Governance, Process Management, Strategic Thinking

Additional Job Details

Address:

20 KING ST W:TORONTO

City:

Toronto

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

GROUP RISK MANAGEMENT

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-01-20

Application Deadline:

2026-11-19

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.

RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

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More about this job

Responsibilities

The manager will oversee the AML model testing process, ensuring code accuracy and reliability through comprehensive unit and integration testing. Additionally, the role involves exploring and implementing AI Agent workflows to automate testing operations and improve efficiency.

Requirements

Candidates must have hands-on experience with SQL, SAS, Python, and Dataiku, along with strong analytical and critical thinking skills. A post-secondary education is required, with a preference for degrees in Statistics, Mathematics, Engineering, or Computer Science.

Skills

SQL
SAS
Python
Dataiku
AML model testing
Code logic validation
Unit testing
Integration testing
AI Agent workflows
Data processing
Analytical skills
Critical thinking
Communication
Collaboration
Regulatory compliance
Machine learning

Benefits

Total Rewards Program
Bonuses
Flexible benefits
Coaching and managing opportunities

Visa sponsorship

Not detected in the job text

Keywords

AML
Model Testing
SQL
SAS
Python
Dataiku
AI Agents
Automation
Quality Assurance
Code Logic
Unit Testing
Integration Testing
Regulatory Compliance
Machine Learning
Data Science
Statistics
Mathematics
Engineering
Computer Science
Risk Management
Financial Regulation
Strategic Thinking
Process Improvement
White Paper
Decision Boundaries

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