Senior Software Engineer, Logging & Experiments

Asana Asana · Enterprise · Vancouver, BC · Infrastructure Engineering

Asana is seeking a Senior Software Engineer for their Data Infrastructure team to scale logging systems and experimentation frameworks. The role involves designing, developing, and maintaining large-scale projects related to logging and experimentation, optimizing in-house frameworks, defining next-generation logging APIs, and curating the observability experience for engineers. The ideal candidate has a strong backend and data-intensive backend background with experience in production-grade systems, distributed systems, or cloud-native infrastructure, and familiarity with data processing, experiment rollouts, or observability platforms. While not core to the role, curiosity about AI tools is a plus.

What you'd actually do

  1. Design, develop, and maintain medium to large-scale projects related to logging and experimentation, acting as a subject matter expert for our Vancouver engineering site.
  2. Scale and optimize our in-house experimentation and feature flagging framework, ensuring reliable, low-latency execution for logic sitting in the critical path of every Asana user session.
  3. Define and implement the next generation of our logging APIs, establishing the high-fidelity data contracts used across the company to architect solutions for unique observability challenges.
  4. Curate the observability experience for Asana’s engineers, working at the interface of vendor capabilities and internal workflows to provide out-of-the-box monitoring and debugging.
  5. Collaborate cross-functionally with Product, Infrastructure, and Data Science teams to align our infrastructure with the evolving needs of Asana’s strategy.

Skills

Required

  • Software, Data, or Infrastructure Engineering background
  • experience shipping production-grade code
  • navigating both application development and data-intensive backends
  • 5+ years of experience designing and shipping production-ready systems
  • focus on building scalable backend services, distributed systems, or cloud-native infrastructure
  • distributed data processing
  • experiment and feature flag rollout systems
  • modern observability and logging platforms

Nice to have

  • curiosity about AI tools and emerging technologies
  • willingness to learn and leverage them to enhance productivity, collaboration, or decision-making
  • solving problems across the stack
  • participating in complex infrastructure rollouts

What the JD emphasized

  • shipping production-grade code
  • building scalable backend services, distributed systems, or cloud-native infrastructure
  • low-latency execution