Senior AI Engineer - AI Platform & ML Engineering

About Aviso Wealth

Aviso is a leading wealth management and investment services provider for the Canadian financial industry, with approximately $145 billion in total assets under administration and management, and over 1,000 employees. We're building a comprehensive, technology-enabled, client-centric wealth services ecosystem. Our clients include our partners, advisors, and investors. We're a trusted partner for nearly all credit unions across Canada, in addition to a wide range of portfolio managers, investment dealers, insurance and trust companies, and introducing brokers. Our partners depend on Aviso for specific solutions that give them a competitive edge in a rapidly evolving, highly competitive industry. Our investment dealer and mutual fund dealer and our insurance services support thousands of investment advisors. Our asset manager, NEI Investments, specializes in investing responsibly. Our online brokerage, Qtrade Direct Investing®, empowers self-directed investors, and our fully automated investing service, Qtrade Guided Portfolios®, serves investors who prefer a hands-off approach. Aviso Correspondent Partners provides custodial and carrying broker services to a wide range of firms. We have offices in Toronto, Vancouver, and Montreal. Aviso is backed by the collective strength of our owners: the credit union Centrals, Co-operators/CUMIS, and Desjardins.

At Aviso, we are dedicated to improving the financial well-being of Canadians. As a leading wealth management organization, we are committed to leadership, innovation, partnership, responsibility, and community.

The Opportunity

We're looking for an AI Engineer, AI Platform & ML Engineering to join our Data & AI Technology Partners team. Reporting to the Sr. Director of Data Science and AI Enablement, the AI Platform & ML Engineering is responsible for focusing on the platform patterns, MLOps practices, model lifecycle, deployment standards, monitoring, evaluation, and governance integration needed to move AI and machine learning solutions beyond experimentation. This is a hands-on engineering role for someone who wants to build the foundation that allows AI solutions to become repeatable, governed, observable, and production ready.

Our Values

We Care – You do the right thing for clients, partners and colleagues. You build trusted relationships, champion service excellence, and contribute to a culture where people feel valued and supported.

We Dare – You challenge the status quo with bold ideas and fresh perspectives. You embrace change, seek opportunities to innovate and are comfortable exploring new ways of working.

We Share – You collaborate openly and build meaningful relationships. You seek out diverse perspectives, share your knowledge and work together to help colleagues, clients and partners succeed.

We Deliver – You take ownership of your work, honour your commitments and focus on delivering meaningful results. You hold yourself accountable and continuously look for ways to improve.

What Your Day Looks Like

• Build reusable AI and ML engineering patterns that help teams move from proof-of-value to production safely and consistently
• Establish practical MLOps and LLMOps practices using Databricks, AWS, MLflow and related platform capabilities
• Create standards and templates for model deployment, serving, monitoring, evaluation, and production release
• Support API integration and deployment patterns for ML, GenAI and agentic solutions
• Partner with Data Engineering & Data Management to define feature engineering data product, and reusable pipeline patterns for AI/ML use cases
• Help define how models, prompts, agents, data products, and AI outputs are versioned, tracked, monitored, and governed
• Partner with Data & AI Governance to embed responsible AI, lineage, access control, auditability, and risk controls into production workflows
• Help monitor AI cost, performance, reliability, usage, and operational risk, while contributing to reusable standards and community learning

Requirements

Education:

• Bachelor's or Master's Degree in Computer Science, Software Engineering, Data Engineering, Data Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, Engineering or related technical field
• Equivalent hands-on experience building data, AI, machine learning, platform, or cloud engineering solutions may be considered in place of formal education

Experience:

• 10+ years of overall experience with 4+ years of experience building, deploying, or supporting machine learning, AI, or data-driven solutions in production environments and 5 to 7 years working in the data space

Certifications:

• Databricks certification related to Machine Learning, Data Engineering, Generative AI or platform administration
• AWS certifications related to cloud architecture, machine learning, AI, DevOps, data engineering or security
• Microsoft Azure certifications related to AI, data, cloud engineering, DevOps, or security
• Other relevant certifications in MLOps, LLMOps, cloud platforms, DevOps, security, architecture, or enterprise AI platforms

Technical Skills:

• Strong Python development skills, especially for ML engineering, automation, APIs, testing and production implementation
• Hands-on experience with cloud-based AI/ML platforms; experience with AWS an asset, Databricks, Azure, MLflow or Lakehouse platforms
• Strong understanding of MLOps, CI/CD/CT, model deployment, model serving, and production release practices for AI and ML solutions
• Experience with model evaluation, validation, monitoring and observability, including model performance, drift, reliability, latency, usage and cost
• Familiarity with LLMOps practices that support GenAI and agentic solutions in production, including prompt/model versioning, evaluation pipelines, controlled releases, and production support patterns
• Experience developing reusable AI/ML platform patterns, including deployment templates, secure serving patterns, feature engineering standards, and integration frameworks
• Understanding of enterprise security, governance, and control requirements for production AI and ML workloads

Soft Skills:

• Strong consultative and communication skills, with the ability to explain technical trade-offs to data, technology, risk, governance, and business stakeholders
• Fluent communication skills in English are required and bilingual skills in French are an asset

Why Aviso Wealth?

• Dynamic and inclusive culture that rewards innovation and celebrates success
• Competitive compensation package that rewards and recognizes individual contributions
• Excellent health, dental and insurance benefits to meet the diverse needs of our employees
• Generous vacation time, fitness benefit, parental leave top-up options
• Matching contributions to our retirement program
• Commitment to the continuous improvement of our staff through learning & development and an education assistance program
• Regular social events to foster teamwork

Compensation

This position is posted with an expected salary range of $135,000 - $150,000 CAD annually. Individual compensation packages are based on various factors unique to each candidate and the requirements of the position.

Equal Employment Opportunity

Aviso welcomes and encourages applications from all qualified individuals including persons with disabilities. If you require an accommodation, we will work with you to meet your needs in all stages of the hiring process.

We thank all applicants for their interest, however, only those selected for further consideration will be contacted.

No recruiters or agencies, please.

Privacy

By submitting your application, you consent to the collection, use, and disclosure of your provided personal information for the purposes of assessing your qualifications and suitability for employment with Aviso. Your information will be handled in accordance with applicable Canadian privacy laws, including the Personal Information Protection and Electronic Documents Act (PIPEDA) and relevant provincial legislation. Your data may be shared with authorized personnel involved in the recruitment process and retained only as long as necessary to fulfill these purposes or as required by law.

Further information is available on the Privacy link on our Career Page – Privacy Policies.