Autodesk's Visualization Solutions power high-performance 2D and 3D visualization experiences across our product portfolio. We are standing up a new team in Canada to bring agentic AI to that experience — expanding our Viewer MCP from a basic capability layer into a production-grade agentic platform that lets users interact with their models in natural language and get intelligent assistance directly inside Autodesk products.

As the Software Development Manager, MCP/AI for this team, you will build it from the ground up and lead it to deliver agentic capabilities that other Visualization Solutions teams — and our customers — build on. You operate at the intersection of engineering execution, people leadership, and AI strategy. You will hire and grow a team that brings machine-learning depth new to the organization, set the technical direction for the agentic platform alongside your senior engineers, and forge the cross-team partnerships that turn it into a true platform.

Success is measured by your ability to build a high-performing team, ship reliable agentic capabilities at a predictable pace, and establish AI/ML as a durable, trusted competency across the org.

• Hire, build, and grow a diverse, high-performing engineering team — including ML/AI talent new to the organization — through coaching, feedback, and performance management.

• Foster a culture of ownership, quality, experimentation, and responsible AI.

• Own delivery of team commitments: plan, prioritize, and ship the Viewer MCP and agentic capabilities predictably and at high quality.

• Set and drive the technical strategy and roadmap for the agentic platform, partnering with your Principal/Senior engineers on architecture and trust models (human-in-the-loop, review gates, traceability, confidence signaling).

• Partner across the Visualization Solutions Org — and with Product, UX, Applied AI, and other platform teams — to expose their capabilities through a shared agentic layer and align on a common direction.

• Establish how the team evaluates AI systems — quality, safety, latency, and cost — and embed evaluation into the delivery process.

• Ensure engineering best practices: code quality, testing, CI/CD, observability, and production support for AI-powered services.

• Identify risks, remove blockers, and communicate progress, trade-offs, and outcomes clearly to stakeholders and leadership.

• Define approaches in a green-field space where established procedures don't yet exist.

• Bachelor's or Master's in Computer Science, Computer Engineering, or equivalent experience.

• 3+ years leading or managing software engineers, plus 7+ years of industry software engineering experience.

• Proven track record delivering complex, production-grade systems and services.

• Experience building or leading teams that ship AI/ML-powered products — e.g. LLM/agentic workflows, recommendation/insights systems, or ML in production.

• Working understanding of LLMs and agentic workflows, and of how to evaluate AI systems.

• Strong grounding in modern software practices: cloud-native architectures, APIs, CI/CD, automated testing, and Agile delivery.

• Excellent communication, collaboration, and stakeholder-management skills.

• Experience standing up or scaling a new team or a new technical competency in an organization.

• Familiarity with the Model Context Protocol (MCP), agent orchestration frameworks, or composable tool/capability architectures.

• Experience with data platforms and ML infrastructure (eval pipelines, feature/data stores, model serving) and with cloud (AWS, containers).

• Familiarity with 2D/3D visualization, CAD/BIM, rendering, or graphics technologies.

• Experience partnering with Applied AI / research teams to bring models into production.

You are an engineering leader who pairs delivery focus with genuine enthusiasm for AI. You can hire and grow people in a domain that is new to the org, create clarity in an ambiguous green-field space, and partner across teams to build something larger than any one team owns. You balance shipping with responsible-AI rigor, you let your technical leaders drive architecture while you ensure alignment and execution, and you are motivated by establishing a trusted, durable AI capability that powers real customer workflows.

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