AI Engineer building production AI, Generative AI, and predictive pricing solutions for RBC Capital Markets. Developing scalable desk - facing tools for Sales & Trading.
About the role
- Senior AI Engineer building governed MLOps and ML platform foundations for Aviso Wealth’s Canadian wealth management ecosystem. Productionizing AI, GenAI, and agentic solutions.
Responsibilities
- 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 and Data Management to define feature engineering data products and reusable pipeline patterns
- Define versioning, tracking, monitoring, and governance for models, prompts, agents, data products, and AI outputs
- Partner with Data and AI Governance to embed responsible AI, lineage, access control, auditability, and risk controls into production workflows
- Monitor AI cost, performance, reliability, usage, and operational risk
- Contribute to reusable standards and community learning
- Report to the Sr. Director of Data Science and AI Enablement
Requirements
- 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
- 4+ years of experience building, deploying, or supporting machine learning, AI, or data-driven solutions in production environments
- 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 for ML engineering, automation, APIs, testing and production implementation
- Hands-on experience with cloud-based AI/ML platforms, AWS, Databricks, Azure, MLflow or Lakehouse platforms
- Strong understanding of MLOps, CI/CD/CT, model deployment, model serving, and production release practices
- Experience with model evaluation, validation, monitoring and observability
- Familiarity with LLMOps practices for GenAI and agentic solutions in production
- Experience developing reusable AI/ML platform patterns
- Understanding of enterprise security, governance, and control requirements for production AI and ML workloads
- Strong consultative and communication skills
- Fluent communication skills in English required; bilingual French is an asset
Benefits
- Competitive compensation package that rewards and recognizes individual contributions
- Excellent health, dental and insurance benefits
- Generous vacation time
- Fitness benefit
- Parental leave top-up options
- Matching contributions to the retirement program
- Learning and development opportunities
- Education assistance program
- Regular social events
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Report this job
Found something wrong with the page? Please let us know by submitting a report below.
Full - stack AI engineer developing agentic applications for Magna’s automotive mobility technology business. Building cloud - deployed workflows, data integrations, and intuitive interfaces for R&D teams.
AI and Automation Leader building secure enterprise AI and automation for Top Aces’ defense training and aircraft sustainment services. Improving aviation readiness, MRO, supply chain, compliance, and corporate productivity.
AI developer building machine - learning models and image datasets for GenAIz's life science and pharmaceutical software. Collaborating with developers, designers, product, business, and architecture teams.
AI Engineer building secure, reliable Azure infrastructure for FacilityOS’s facilities - operations SaaS platform. Supporting Terraform, CI/CD, observability, security, incident response, and FinOps.
Lead AI Engineer building secure AWS AI, ML, and GenAI solutions for Sun Life’s financial - services business. Delivering Bedrock applications, RAG pipelines, intelligent agents, and enterprise automation.
AI Engineer building AWS - based GenAI applications, RAG solutions, and intelligent agents for Sun Life’s financial security and health services. Collaborating across technology and business teams in a hybrid environment.
Senior AI Engineer building secure, production - grade AI, ML, and GenAI solutions on AWS for Sun Life’s financial security and health business. Delivering RAG, intelligent agents, automation, and reusable enterprise platforms.
AI/ML Software Engineer shaping AI strategy and building scalable AI/ML components. Developing solutions atop Smile Digital Health’s FHIR - based healthcare data platform.
Senior AI Engineer building production Agent and RAG systems for NetBrain’s no - code network automation platform. Improving LLM reliability, observability, and automation at enterprise scale.