As a leading wealth management organization, we are committed to leadership, innovation, partnership, responsibility, and community. We’re looking for an AI Engineer, AI Platform &

• ML Engineering to join our Data &

• AI Technology Partners team. 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. You seek out diverse perspectives, share your knowledge and work together to help colleagues, clients and partners succeed 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 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 ~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 ~ 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 ~ 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 ~ 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 Excellent health, dental and insurance advantages 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 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 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. 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 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.

This position is posted with an expected salary range of $135,000 - $150,000 CAD annually.

📌 Senior AI Engineer - AI Platform & ML Engineering-229 (Toronto)
🏢 Aviso
📍 Toronto