Principal MCP/AI Developer

Job Requisition ID # 26WD99362 Position Overview Autodesk '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) into a production-grade agentic platform that lets users interact with their models in natural language and that other Visualization Solutions teams build on. As the Principal MCP/AI Developer, you will define and drive the technical direction of that platform — its capability/tool model, agent-orchestration architecture, trust model, and the way we evaluate and operate AI in production. You operate on highly complex, ambiguous problems that span systems, domains, and teams, and you bring deep applied-ML and ML-systems expertise . You are the technical authority who sets the bar for responsible and reliable AI, and multiplies the impact of every engineer on the team. Responsibilities - Define and drive the technical strategy for the agentic platform: the MCP tool/capability model, agent-orchestration architecture, context/memory, retrieval, and trust model. - Frame and prioritize the highest-impact AI problems, aligned with product and platform strategy, and turn ambiguity into clear, executable plans. - Establish the evaluation and quality framework for AI systems — accuracy, safety, latency, cost — and the practices for fine-tune-vs-prompt and model-selection decisions. - Set the architecture for trust: traceability, auditability, reversibility, human-in-the-loop, and confidence signaling, as platform-wide standards. - Lead the design and delivery of large, cross-team initiatives that span multiple products and services; influence and align teams across the Visualization Solutions Org. - Drive adoption of shared agentic capabilities, frameworks, and patterns; raise engineering standards and ML maturity across the org. - Act as technical authority for critical decisions and trade-offs across performance, scalability, cost, and developer experience. - Mentor senior engineers, partner with Product/UX/Applied AI on long-term roadmap, and stay hands-on in the most critical areas of the system. Minimum Qualifications - Bachelor's or Master's in Computer Science / Computer Engineering, or equivalent experience. - 8–12+ years of software engineering, including significant work on large-scale or platform systems. - Deep, hands-on experience building and operating AI/ML systems in production — LLMs, agents, orchestration, RAG — including evaluation , model selection, and fine-tune-vs-prompt trade-offs. - Expert proficiency in TypeScript/JavaScript and modern web technologies; strong architecture skills across distributed systems, APIs, and composable services. - Proven ability to lead cross-team technical initiatives and influence without direct authority. - Demonstrated ability to operate independently in highly ambiguous problem spaces. - Excellent communication skills with the ability to influence senior stakeholders. Preferred Qualifications - Deep familiarity with the Model Context Protocol (MCP), agent frameworks, and composable tool/capability architectures. - ML-systems / ML-infrastructure expertise — eval pipelines, vector/retrieval infrastructure, model serving, data platforms. - Experience building or evolving platform ecosystems (APIs, extensibility, developer platforms). - Track record of leading major technical transformations or introducing a new technical competency to an organization. - Expertise in 2D/3D visualization, rendering engines, or graphics technologies. The Ideal Candidate You are a deeply experienced engineer who thinks in systems and platforms and brings deep, hard-to-find AI/ML expertise. You are comfortable in ambiguity; you frame the right problems, and you lead complex initiatives from concept to production. You balance shipping with responsible AI rigor; you set