Senior Backend Engineer (Java) - AI Media Transforms (m/f/x) at Canva in Vienna

  • Company: Canva
  • Location: Vienna, at
  • Job type: full time
  • Workplace: onsite
  • Posted: 2026-09-10

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Job description

Join the team redefining how the world experiences design. Servus, hey, g'day, mabuhay, kia ora, 你好, hallo, vítejte! Thanks for stopping by. We know job hunting can be a little time consuming and you're probably keen to find out what's on offer, so we'll get straight to the point. Where and how you can work Our flagship campus is in Sydney, Australia but Austria is home to part of our European operations. And you have choice in where and how you work, we trust our Canvanauts to choose the balance that empowers them and their team to achieve their goals. Fun fact, a big part of our Austrian operations is developing the AI product within Canva to help reimagine how artificial intelligence can be used in design. Pretty cool ha! What you’d be doing in this role As Canva scales change continues to be part of our DNA. But we like to think that's all part of the fun. So this will give you the flavour of the type of things you'll be working on when you start, but this will likely evolve. At the moment, this role is focused on: Own the backend of the service that every AI editing feature at Canva calls. It's a Java service that sits between Canva's product surfaces and our GPU model workers, and it turns "remove this background" into a durable, observable, safe job. You'll own API and proto design, the job and task state machine, multi-step pipelines, queue-driven worker orchestration, persistence, content safety and moderation, and the error handling that makes a multi-second GPU-backed request feel reliable. The models are built by our ML engineers and research partners; you own everything around them. Ship new editing capabilities end to end. When a new model is ready (e.g., inpainting, upscaling, background removal, and several more each year) you design the API, build the pipeline, wire up the async handoff to the GPU worker, and roll it out behind feature flags with metrics from day one. Run it in production. You'll be on call for a service doing GPU-backed work at Canva scale, and you'll own what that requires: autoscaling driven by queue depth, GPU capacity and instance-type choices, replica floors and warm pools for latency-sensitive models, health probes, region rollouts, release schedules and deploy tests, plus the dashboards you'll wish you had at 2am. Make it faster and cheaper. Profile the whole request path including queue wait, media fetch, pre- and post-processing, GPU time, moderation, S3 upload and ship improvements to both latency and cost per request. Most of the wins here are in Java, orchestration and capacity, not in the model. Build the platform other teams build on. Several internal services and product surfaces call these APIs, from Canva AI and Design Agent to the editor, and the photo editor. You'll design contracts that survive constant model churn: backwards-compatible proto evolution, sensible defaults, completion and notification semantics callers can rely on, and requirements like content provenance, privacy preferences and data-eligibility checks built into the pipeline rather than bolted on later. Set backend direction and raise the bar. You'll act as the backend tech lead for the team, shaping architecture and design reviews alongside the team's ML tech lead, and raising backend craft across a team of both backend and ML engineers. Partner across teams. Product teams on requirements, our research partners on new models, the inference team on GPU serving, and consumer teams on landing new capabilities on the platform. You're probably a match if You have significant commercial experience designing, building and operating backend systems in production — and staying on call for them. You have high proficiency in Java or a similar JVM language (Kotlin, Scala), with a solid grasp of the surrounding ecosystem and tooling. You have strong computer science fundamentals such as concurrency, distributed systems, performance engineering, and the design patterns that come with running services at scale. You've b

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