Canva

Staff Software Engineer - Experiments Platform

Canva

Remote · Full Time

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Any
Salary
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Openings
1
Posted
1 day ago
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Job description

Company Overview and Work Environment

Canva is a leading design platform offering flexible working options. Our main campus is in Sydney with additional locations in Melbourne, Brisbane, Perth, and Adelaide. This role supports remote work within Australia, allowing work from home, offices, or a combination tailored to your and your team's preferences.

Role Summary

We're looking for a Staff Software Engineer to lead backend systems supporting Canva's experimentation platform, which is integral to how we deliver product improvements. You will enhance the tools used to configure experiments, target users, manage variants, and analyze results, ensuring these processes are secure, intuitive, and effective. Part of the role involves developing capabilities that go beyond reporting results, including faster signal detection, early alerts on issues, and AI-driven analysis to accelerate learning and iteration.

Key Responsibilities

  • Provide senior technical leadership on backend systems powering experimentation at Canva.
  • Collaborate closely with senior leaders and platform teams to address substantial technical challenges and guide the future direction of the experimentation platform.
  • Drive improvements to ensure platforms support good experimentation practices and user needs at scale.

Required Experience and Skills

  • Proven backend platform engineering experience creating critical systems relied upon by other engineers.
  • Exposure to large-scale experimentation or A/B testing frameworks, feature management, or progressive rollout systems within sizable engineering organizations.
  • Demonstrated ability in technical leadership: resolving ambiguous engineering problems and guiding teams towards clear outcomes.
  • Experience driving adoption of internal platforms by ensuring trust and usability across teams.
  • Strong fundamentals in backend and distributed system design, including scalability, availability, consistency, and failure handling.
  • Understanding of data engineering or analytics to comprehend how experimentation data flows and is utilized.
  • Familiarity with experimentation principles: experiment assignments, targeting, feature flags, metrics, guardrails, and progressive rollout strategies.
  • Proficiency in software engineering with possible experience in Java; however, strong engineering fundamentals capable of transferring across languages are most vital.

Preferred Qualifications

  • Previous direct involvement in building or designing experimentation, A/B testing, or feature management infrastructure.
  • Combination of software engineering and data-related experience such as data science, data engineering, or analytics engineering.
  • Experience implementing feature flagging, user targeting, progressive rollout, or automated guardrails.
  • Comfortable working alongside data scientists with a sound understanding of experimentation statistics.

About the Team

You will be part of the Rollout Insights subgroup responsible for delivering Canva's experimentation capabilities. The team integrates software engineering and senior data science expertise and collaborates widely across engineering and data science units, supporting product decisions with data-driven insights. This is a high-growth area critical to company priorities with ongoing substantial platform development opportunities.

Additional Information

At Canva, your hard work is accompanied by moments of inspiration, social connection, and enjoyment. Benefits include equity participation, inclusive parental leave policies, an annual allowance for wellbeing and workspace setup, and flexible leave provisions.

Recruitment Notes

Our hiring process embraces AI-driven technical challenges reflecting real work scenarios. We welcome diversity of skills and backgrounds and encourage everyone to apply, sharing your pronouns and requesting reasonable accommodations if needed. Interviews are conducted virtually.

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