Senior Applied AI Engineer

BMO Financial Group

Toronto, CAonsite$103k-$192k/yrPosted Jun 9, 2026
Posting intelligenceActively listedReposted 4×, possible evergreen/ghost posting

Skills

scikitlearnkubernetestensorflowlangchainairflowpytorchdockerpythonopenaiazurecicdgooglecloudawsml

About the role

Application Deadline:

06/29/2026

Address:

100 King Street West

Job Family Group:

Data Analytics & Reporting

The Senior Applied AI Engineer is responsible for designing, developing, and deploying advanced Gen AI and machine learning solutions that

drive business value in Wealth Management. This role blends deep technical expertise with financial domain knowledge, collaborating with

cross-functional teams to deliver scalable, secure, and compliant AI products. The engineer will design and implement GenAI and agent-based

systems to enhance advisor workflows, client engagement, and operational efficiency.

Key Responsibilities

Contribute to the overall Wealth Management AI strategy formulation and execution

Architect and build GenAI-powered applications for Wealth management use cases.

Liaise with relevant technology teams to build and deploy Gen AI solutions

Lead the solution development, from ideation to prototyping and liaise with our partners to facilitate production and monitoring.

Collaborate with product managers, data scientists, engineers, and business stakeholders to translate requirements into technical solutions.

Integrate AI solutions with existing platforms (CRM, portfolio management, data warehouses) and ensure interoperability.

In collaboration with the risk and RAIOps teams, ensure all AI solutions meet performance, security, and regulatory standards.

Leverage best practices in MLOps, model governance, and responsible AI.

Stay current with industry trends, emerging AI technologies in financial services AI.

Document technical designs, create demos, and support enablement and adoption across the organization.

Required Skills and Tools

Advanced proficiency in Python and machine learning frameworks (TensorFlow, PyTorch, scikit-learn).

Experience building Copilot Studio Agents.

Proficiency with GenAI, LLMs (e.g., OpenAI, Google Gemini, Anthropic), and agent orchestration frameworks (LangChain,

LangGraph, AutoGen).

Strong understanding of cloud platforms (Azure, AWS, GCP) and MLOps tools (MLflow, Kubeflow, Airflow).

Familiarity with financial services workflows, data privacy, and compliance requirements.

Strong hands-on experience with both AWS and Azure cloud environments, including their AI/ML, data, and deployment

toolsets (e.g., SageMaker, S3, Lambda, Azure Functions, Azure ML, Blob Storage)

Proficiency with Kubernetes for container orchestration and deployment of scalable AI solutions.

Experience with Docker, and CI/CD pipelines

Expertise in data engineering, model deployment, and monitoring.

Knowledge of API integration, microservices, and scalable system architecture.

Excellent problem-solving, communication, and stakeholder management skills.

Qualifications:

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.

10+ years of experience in AI/ML engineering, with at least 2 years in financial services or regulated industries or a combination of relevant experience and education.

Proven track record of designing and deploying production-grade AI solutions.

Experience working in Agile teams and collaborating with cross-functional stakeholders.

Demonstrated ability to mentor and lead technical teams.

Advanced level of proficiency:

Gen AI, Mathematics

Critical thinking.

Creative reasoning.

Computational Thinking and Programming.

Deep Learning.

Machine Learning.

Scaling Models.

Continuous Integration and Continuous Delivery/Deployment.

ML algorithm.

Verbal & written communication skills.

Analytical and problem solving skills.

Influence skills.

Collaboration & team skills; with a focus on cross-group collaboration.

Able to manage ambiguity.

Salary :

$103,200.00 - $192,000.00

Pay Type:

Salaried

The above represents BMO Financial Group’s pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position.

BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards

Compensation

This Machine Learning Engineer role pays $103k-$192k/yr. Within typical range for machine learning engineer roles in Canada.

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