Senior Software Engineer, Canvas Core

Responsibilities

• Own and deliver Canvas platform capabilities from problem definition through implementation, release, measurement, and iteration.
• Design and build maintainable systems for real-time collaboration, shared document editing, spatial interactions, rendering performance, asset management, and developer APIs.
• Develop API contracts, service boundaries, data models, validation, versioning, error handling, documentation, and platform integrations.
• Improve performance through profiling, bottleneck analysis, architectural simplification, and optimization of critical interaction paths.
• Build and evolve hierarchical document and scene structures, spatial indexing and querying, layout behavior, asset management, and selection mechanics.
• Contribute to AI-enabled product capabilities involving the canvas, document model, collaboration systems, or developer platform.
• Participate in technical design reviews, demos, code reviews, mentoring, documentation, and engineering-practice improvements.
• Partner with Product, Design, Engineering, and other stakeholders to deliver reliable and intuitive editor experiences.

Requirements

• Fluency in modern JavaScript and TypeScript, with familiarity in React, Node.js, or comparable modern frameworks.
• At least 6 years of experience building and shipping large-scale production software as part of an agile engineering team.
• Experience designing scalable, reliable, high-performance systems and developer-facing abstractions.
• Experience designing clean API contracts and service boundaries, including data models, versioning, validation, error handling, documentation, and maintainability.
• Experience with distributed, concurrent, collaborative, or low-latency systems and concepts such as synchronization, consistency, event ordering, latency, failure modes, and performance trade-offs.
• Experience with performance optimization, including profiling, bottleneck analysis, memory and CPU efficiency, latency reduction, and responsiveness.
• Practical experience using AI-assisted tools to prototype, implement, test, document, and measure engineering work.
• Strong communication and collaboration skills, including a low-ego approach and the ability to contribute to technical discussions and team practices.
• Exposure to rich object models, parallel processing, off-main-thread architectures, rendering pipelines, background computation, or multithreaded systems is a plus.
• Interest in or hands-on experience building or integrating AI-enabled product capabilities is valued.
• Comfort working in high-growth, fast-paced environments or scale-ups is a plus.