Senior Software Engineer, Canvas Core - Mural

About the Team

The Canvas Core team builds and maintains the foundational platform that powers Mural’s visual thinking experience. This includes the infinite canvas, key editor components, document editing behaviors, asset management, real-time collaboration, and the systems that enable fast, reliable, and intuitive interaction on the canvas.

We’re also responsible for the Mural UI, the real-time message protocol that enables seamless remote collaboration, and the developer-friendly APIs that internal teams use to build features like diagramming, workshops, presentations, integrations, and AI-enabled product capabilities.

Our mission is to ensure the Mural editor is fast, reliable, intuitive, and easy to build on. We prioritize performance, simplicity, developer experience, and platform quality.

Your Mission

As a Senior Software Engineer, you’ll help design, build, and improve the Canvas platform so that the Mural editor remains reliable, high-performing, and intuitive for our users.

You’ll work on the systems that power real-time collaboration, shared document editing, spatial interactions, rendering and interaction performance, asset management, developer APIs, and AI-enabled product capabilities across the Mural editor.

Your role will be to reduce platform complexity, improve the quality and speed of Canvas development, and help teams ship high-quality editor experiences quickly and safely. You’ll partner closely with Product, Design, Engineering, and other stakeholders to turn ambiguous product and platform problems into clear, maintainable technical solutions.

What You'll Do

• Own and deliver new Canvas platform capabilities and improvements from problem definition through implementation, release, measurement, and iteration.
• Partner with Product and Design to shape high-quality user experiences, balancing pragmatic technical delivery with long-term platform needs.
• Design and build maintainable Canvas platform systems, with accountability for quality, performance, reliability, and developer experience.
• Contribute to developer-friendly APIs, service boundaries, and platform contracts that internal teams can build on quickly and safely.
• Use AI-assisted tools and agentic workflows as part of your engineering practice to prototype, implement, test, document, and measure work effectively.
• Strengthen the team through technical design reviews, demos, code reviews, mentoring, and improvements to engineering practices.
• Build and evolve canvas systems with rich document and object models, including hierarchical scene or document structures, spatial indexing and querying, layout behavior, asset management, and selection mechanics.
• Work on large-scale concurrent and real-time collaboration systems that keep shared documents synchronized across users.
• Help design, build, and integrate AI-enabled product capabilities where they intersect with the canvas, document model, real-time collaboration systems, or developer platform.
• Improve performance through profiling, bottleneck analysis, architectural simplification, and targeted optimization.

What You'll Bring

• Fluency in modern JavaScript/TypeScript, with familiarity in React, Node.js, or comparable modern frameworks.
• 6+ years building and shipping large-scale production software as part of an agile engineering team.
• Strong engineering judgment with experience designing and delivering scalable, reliable, high-performance systems and developer-facing abstractions.
• Experience designing clean API contracts and service boundaries, including data models, versioning, validation, error handling, and documentation.
• Experience building distributed, concurrent, collaborative, or low-latency systems (e.g., collaboration tools, shared-state systems, messaging protocols).
• Exposure to complex systems with rich object models, spatial indexing, layout behavior, and selection mechanics.
• Interest in AI-enabled product capabilities or hands-on experience integrating them in production.
• Performance optimization experience, including profiling, bottleneck analysis, memory/CPU efficiency, and latency reduction.
• Practical experience using AI-assisted tools to prototype, implement, test, document, and measure engineering work.
• Low-ego approach to working cross-functionally with Product, Design, and Engineering.