At Sisu, we're building a software platform that empowers people to make better decisions using data. Based on years of cutting-edge research at Stanford, Sisu enables users to quickly and comprehensively understand what’s driving their key metrics, so they never miss a window of opportunity to act.

Sisu is a fundamental rearchitecture of how users interact with data. Instead of relying on users to tell us what they want to see, as in traditional dashboarding systems, Sisu predicts users’ intent based on their metrics of interest, and past behaviors. We take this kind of predictive analysis for granted in consumer applications (e.g., Netflix, Google, Facebook), but the hardest interface design and ranking problems lie in making private data found in everyday organizations actionable. The key problem we’re solving as a first step in this direction is to help identify what’s driving change in key metrics like revenue, retention, and churn among the enormous set of factors like user demographics, campaigns, and acquisition channels. To do so, we combine statistical analysis and machine learning at scale to provide users personalized, real-time diagnoses of changes in their metrics via an explainable, interpretable user interface.

As the founding member of our DevOps team, you’ll own and shape our multi-cloud, multi-region deployment architecture, release process, automated testing infrastructure, metrics & monitoring infrastructure, incident management process, developer experience, and more. We'll look to you for leadership over our infrastructure and the future direction of the team. You'll solve critical technical problems that will enable the Sisu team to solve problems more quickly and efficiently.

Responsibilities

• Design and automate our multi-cloud, multi-region production environment
• Streamline our release process, helping us evolve to zero-downtime continuous deployment
• Build out our automated testing infrastructure, including unit testing, integration testing, load testing, canary testing, frontend scenario testing, and more
• Iterate on our metrics & monitoring infrastructure, along with our incident management process
• Shape the engineering culture through mentorship and technical leadership
• Work collaboratively with multiple departments such as Product Engineering, Platform Engineering, Machine Learning, Security, Sales, Marketing, and G&A

Preferred Qualifications

• Experience with container orchestration technologies like Kubernetes and Docker
• Experience in cloud environments such as AWS, Azure or GCP
• Fluency with a scripting language (e.g. Python)