Senior Engineering Manager (be/ml) - Context & Personalisation

Canva Canva · Enterprise · Melbourne, VIC, Australia · Information Technology

Senior Engineering Manager to lead the Context & Personalisation team within Canva's AI Supergroup. This role focuses on building systems that apply user context, preferences, brand signals, and history to create personalized AI experiences. Responsibilities include leading a multidisciplinary team, defining strategy and roadmap for the context platform, developing capabilities like AI Memory and brand-aware generation, designing scalable APIs, and driving adoption of AI features across Canva's ecosystem.

What you'd actually do

  1. Leading and coaching a multidisciplinary team of backend and machine learning engineers building Canva’s context and personalisation systems
  2. Defining and delivering the strategy and roadmap for Canva’s centralised context platform and personalisation infrastructure
  3. Developing capabilities such as AI Memory, custom instructions, and brand-aware AI generation that make Canva AI feel deeply personal
  4. Designing scalable APIs and platform primitives that allow internal teams across Canva to build AI-powered experiences quickly and safely
  5. Partnering closely with Product and Design leaders to identify high-impact opportunities to elevate Canva AI experiences

Skills

Required

  • experienced engineering leader
  • built or scaled platform systems, developer infrastructure, or shared services
  • strong technical depth with product thinking
  • experience working in or alongside AI, machine learning, recommendation systems, or data-driven platforms
  • comfortable operating in high-ambiguity, fast-moving environments
  • developing engineers and building high-performing teams

Nice to have

  • Experience building context systems, recommendation engines, or personalisation pipelines
  • Experience working on platforms that serve multiple internal teams or product surfaces
  • Experience operating in high-growth product environments balancing platform investment and feature delivery

What the JD emphasized

  • AI capabilities
  • user context
  • personalised AI experiences
  • AI Memory
  • brand-aware AI generation
  • AI-powered experiences
  • AI landscape

Other signals

  • leading a team
  • defining strategy and roadmap
  • building AI memory, custom instructions, brand-aware AI generation
  • designing scalable APIs and platform primitives
  • partnering with Product and Design
  • driving adoption of AI capabilities
  • growing and developing a high-performing engineering team