Software Developer

Position OverviewAutodesk's Visualization Solutions power high-performance 2D and 3D visualization experiences across our product portfolio. Our new team in Canada is bringing agentic AI to that experience - expanding our Viewer MCP (Model Context Protocol) from a basic capability layer into a production-grade agentic platform that lets users interact with their models in natural language.As an MCP/AI Developer you will build end-to-end features of that platform: MCP tools, agentic workflows, and the services behind them. You'll work hands-on across a modern, cloud-enabled web stack, integrating LLMs and models through APIs to deliver capabilities our users rely on. This is a strong software-engineering role with a clear runway to grow deep ML expertise as the team - and the org's AI competency - matures.ResponsibilitiesImplement and maintain clean, well-tested code for MCP tools, agentic features, and their supporting services (front-end and back-end), to team standards.Integrate LLMs and models via APIs/SDKs to deliver agentic workflows, with attention to correctness, latency, and cost.Help build the guardrails of agentic workflows - human-in-the-loop steps, traceability, and clear error handling.Contribute to automated tests, evaluation harnesses for AI behavior, CI/CD pipelines, and developer tooling.Debug and troubleshoot across the stack (agent/tool logic, APIs, web UI), collaborating with senior engineers and QA.Work with Product and UX to translate requirements into technical tasks; surface risks and blockers early and seek mentorship.Minimum QualificationsMaster's in Computer Science / Computer Engineering, or a Bachelor's with 3+ years of relevant experience, or equivalent practical experience.Hands-on experience building software in at least one mainstream language (TypeScript/JavaScript preferred for our stack).Familiarity with modern web development (HTML/CSS/JS) and a framework such as React.Sound understanding of testing, debugging, and code review; experience with Git and collaborative workflows (PRs, branches).Exposure to building with LLMs or AI APIs - e.g. prompting, calling model/agent APIs, or simple agentic/RAG features (course, side-project, or work experience all count).Strong problem-solving skills, eagerness to learn ML/AI deeply, and a collaborative mindset.Experience with Agile practices; strong written and spoken English.Beneficial QualificationsNode.js back-end development and RESTful APIs.Familiarity with the Model Context Protocol (MCP), agent frameworks, or tool-calling patterns.Cloud and CI/CD basics (AWS, Docker, GitHub Actions) and observability tooling.Foundational ML knowledge (embeddings, vector search/RAG, model evaluation).Exposure to 2D/3D rendering, visualization, or graphics concepts (WebGL/WebGPU).The Ideal CandidateYou are a strong, hands-on engineer who is genuinely excited about AI and eager to go deep. You take ownership of features, write quality code, and communicate trade-offs clearly. You learn fast, ask good questions, and are motivated by building agentic capabilities that put powerful AI in the hands of real users.Operationally-focused Professional role, requiring experience OR analytical advisor role still developing higher-level expertise.Solve a range of problems of mild-to-moderate complexity and scope by analyzing possible solutions using standard procedures.Exercise judgement within defined guidelines or known precedents.Seek guidance on unusual situations or circumstances where guidelines are unclear.Receive a moderate level of guidance and direction, with little or no direction day-to-day assignments.Work is typically reviewed by a more experienced team member before it is provided to senior leaders.A common career stabilization point (AKA the "full-contributor" level) for operationally-focused roles, whereas analytical advisor roles at this level are building knowledge of the subject-matter area, function/BU, company, products, and customers.