AI Engineer at Morningstar in Toronto, Ontario, Canada

AI Engineer Location: Toronto About the Team The AI Accelerator team sits at the center of Morningstar’s Generative AI strategy for the Direct Platform. We build and scale core systems such as the Morningstar MCP Server, MCP Gateway, and Morningstar Agent. Our team is responsible not only for delivering GenAI capabilities, but also for solving the underlying challenges that make them production-ready—document vectorization, caching strategies, system scalability, security, and reliability. We work closely with the Morningstar Responsible AI Council to ensure our systems meet strict standards around guardrails, PII filtering, moderation, and anonymized evaluation pipelines. We operate with a strong engineering culture: we question assumptions, prioritize impact over process, and focus on solving meaningful problems rather than executing predefined tasks. Collaboration, shared ownership, and continuous learning are central to how we work. About the Role As a Software Engineer on the AI Accelerator team, you will help design, build, and scale the core services powering Morningstar Directs’ GenAI capabilities. You will work across the full development lifecycle—from ideation and design to implementation, deployment, and iteration. You’ll leverage modern AI-assisted development tools (e.g., GitHub Copilot, Claude Code) to accelerate delivery while maintaining high standards for code quality, testing, and documentation. You will collaborate closely with product managers, designers, and engineers to build systems that are both technically robust and highly valuable to users. This role is ideal for someone who is naturally curious, enjoys exploring new technologies, and takes initiative in learning beyond immediate requirements. Location: Toronto, Ontario (Hybrid policy, 4 days onsite required) What You’ll Do Design, build, and enhance scalable services powering the MCP Server, MCP Gateway, and AI Agent Own features end-to-end, from concept through production deployment and monitoring Collaborate with product and design partners to deeply understand user needs and deliver meaningful solutions Contribute to architectural decisions and continuously improve system design and engineering practices Write clean, maintainable, and well-tested code with a focus on performance and scalability Use logging, monitoring, and debugging tools to maintain high system reliability Evaluate new tools and technologies pragmatically, balancing innovation with real product value Create and maintain clear technical documentation and user-facing guides Mentor teammates and contribute to a culture of knowledge sharing and continuous improvement What We’re Looking For Strong collaboration and communication skills; direct, thoughtful, and transparent in discussions 3+ years of experience with at least one modern object-oriented programming language Solid understanding of computer science fundamentals (data structures, algorithms, design patterns) Experience building production grade applications using AI-assisted development tools (e.g., GitHub Copilot, Claude Code) Experience building production-grade services using GenAI/agent frameworks (e.g., LangChain, AWS Bedrock, Copilot Studio) Experience with containerization and deployment (e.g., Docker) Experience building and operating production systems, including debugging and troubleshooting Experience with relational databases such as PostgreSQL or MSSQL Familiarity with cloud platforms (AWS preferred: EC2, RDS, S3, API Gateway) Experience working in Agile environments and using tools like Jira Nice to Have Experience with Python and the PostgreSQL ecosystem Experience with event-driven systems, queues, and ETL pipelines Familiarity with vector databases and MCP-based architectures Interest in financial markets, investing, or fund research Base Salary Compensation Range $106,037.00 - $ 126,094.00 Incentive Target Percentage 7.5% If you receive and accept an offer from us, we require that personal and any related investments be disclosed confidentiality to our Compliance team (days vary by region). These investments will be reviewed to ensure they meet Code of Ethics requirements. If any conflicts of interest are identified, then you will be required to liquidate those holdings immediately. In addition, dependent on your department and location of work certain employee accounts must be held with an approved broker (for example all, U.S. employee accounts). If this applies and your account(s) are not with an approved broker, you will be required to move your holdings to an approved broker. Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.