Principal Solution Engineer, Ecosystem

Canva · Enterprise · San Francisco, CA · Information Technology

Principal Solution Engineer for Canva's Ecosystem platform, focusing on integrating agentic AI systems with visual design. This role drives technical decisions and alignment between partners (like OpenAI, Google, Microsoft) and Canva engineering, sets technical direction for external platform surfaces, and grounds partner conversations in working code. The engineer will work across MCP, REST APIs, and Apps platform to ensure coherence and carry platform direction outward early. They will also shape strategic partner and customer engagements, leading technical relationships end-to-end.

What you'd actually do

  1. Drive decisions and alignment across Partners and Canva engineering.
  2. Set technical direction for Canva's external platform surface.
  3. Ground partner conversations in working code.
  4. Drive product-line engineering across our external platform surfaces.
  5. Carry the platform direction outward early.

Skills

Required

  • 10+ years of software engineering experience
  • Experience in roles operating at the seam between partner engineering, platform engineering, and product
  • Built developer platforms and shipped code in production on platforms used by external developers
  • Ability to move fluidly between product roadmap, system design, and partner negotiation
  • Ability to bring a prototype or sample code to a hard conversation
  • Technically deep on the modern AI platform stack
  • Experience with MCP, tool-use, agentic API design
  • Direct communication and clear writing
  • Experience with heterogeneous and fast-moving product stacks
  • Ability to quickly orient in unfamiliar codebases
  • Ability to raise the technical bar by sharing knowledge and feedback

Nice to have

  • Hands-on experience shipping or integrating with MCP (Anthropic, OpenAI, Copilot, or Gemini flavours)
  • Strong TypeScript
  • Comfortable across front-end (React) and server-side JavaScript
  • Ability to read Java backend code
  • Track record of turning ambiguous partner signal into crisp engineering decisions

What the JD emphasized

  • technical detail on both sides and translate without losing precision
  • partner signal and engineering reality
  • working code as the proof point
  • partner decision backed by a runnable artifact
  • agentic AI story is delivered across MCP, REST APIs, Apps-in-Canva, and the middleware PaaS
  • technical relationship end-to-end
  • product shape, engineering feasibility, and partner intent in the same conversation
  • technical deep on the modern AI platform stack
  • agentic API design
  • heterogeneous and move fast
  • orient yourself quickly in a codebase you didn't write
  • partner facing wins
  • Hands-on experience shipping or integrating with MCP (Anthropic, OpenAI, Copilot, or Gemini flavours)
  • turning ambiguous partner signal into crisp engineering decisions

Other signals

  • driving technical decisions
  • grounding partner conversations in working code
  • shaping strategic partner and customer engagements
  • technical depth on modern AI platform stack