Senior AI Engineer - AI Platform & ML Engineering

Aviso Wealth:

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. Working with talented and energetic professionals who exemplify our values every day, you will quickly notice that our people and dynamic ‘oneaviso’ culture sets us apart. If you are looking for interesting and challenging work, at a company committed to its people, find out more about what Aviso has to offer at

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.

As oneaviso:

• 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 AL 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

Your experience and skills:

• 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, Dev Ops, data engineering or security
• Microsoft Azure certifications related to AI, data, cloud engineering, Dev Ops, or security
• Other relevant certifications in MLOps, LLMOps, cloud platforms, Dev Ops, 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…