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Morningstar in Toronto is seeking a Senior Software Engineer to build applied systems that bring AI capabilities into production: the data pipelines, LLM integrations, agentic workflows, tool interfaces, and evaluation frameworks that make AI-driven products reliable enough to depend on.
This is applied engineering rather than research; success is measured in shipped, maintainable systems in a fast-changing AI landscape.
Morningstar unites problem solvers with a clear goal: helping investors achieve their financial objectives. As a leading investment research and data company, we stand out by how we apply our insights to serve a broad range of users. Our independent investment research, powered by cutting-edge technology and design, provides tailored solutions that meet users' needs. With a strong foundation in data and innovation, we deliver comprehensive services to investors worldwide, empowering better decisions for individuals and those managing money for millions.
Morningstar unites problem solvers with a clear goal: helping investors achieve their financial objectives. As a leading investment research and data company, we stand out by how we apply our insights to serve a broad range of users. Our independent investment research, powered by cutting-edge technology and design, provides tailored solutions that meet users' needs. With a strong foundation in data and innovation, we deliver comprehensive services to investors worldwide, empowering better decisions for individuals and those managing money for millions.
We are seeking a Senior Software Engineer to build the applied systems that bring AI capabilities into production: the data pipelines, LLM integrations, agentic workflows, tool interfaces, and evaluation frameworks that make AI-driven products reliable enough to depend on. This is applied engineering rather than research; success is measured in shipped, maintainable systems. You may be a strong fit if you love working within a landscape that changes quickly, creating durable architectures with swappable parts, so new models and techniques are adopted on evidence.
The role encompasses fluency across cloud architecture and local model inference, evaluation design, agentic workflows and orchestration, API and tool design, and AI-assisted data