Name: Andrew Conner
Role: Co-founder, Head of Engineering
Joined: September 2019
Past Experience:
Our focus in 2021 has been iterating product development, building integrations to ingest health-related data, scaling our data processing capabilities, and maintaining reliable systems. We've added 6 engineers in 2021 (12 total engineers), and will continue our team growth into 2022. Key recent engineering hires include Scott Klein (Founder/CEO StatusPage, acquired by Atlassian) and Helena Belloff (Icahn School of Medicine Data Scientist). We've been able to continue to attract world-class talent, including former founders and technical leads.
To date, we have built a HIPAA-compliant infrastructure that is able to process hundreds of millions of data points and generate personalized, real-time insights. We've also built a telemedicine consultation process so our customers can easily access regulated medical hardware. Importantly, we've designed for scale: Levels is only successful with our vision if we're prepared to support millions of members. Based on experience at leading tech companies, we've built reliable deployment, monitoring, and observability infrastructure.
Our engineering team has extensive experience building and scaling highly reliable, consumer web and mobile products. We are a product driven team, and have hired for vision alignment—we're solving a large, critical health problem—and specific domain expertise. We have effectively scaled our processes using autonomous teams that ship products end to end, and care deeply about development velocity so we can experiment cheaply and easily. Our mobile app has daily internal releases, and our backends are deployed many times per day. As with the rest of Levels, we operate asynchronous-first, and have minimal meetings (<1 engineering group meeting per week). We are a geographically distributed team, with engineers currently located in US, Canada, Portugal, and Colombia.
Our Data Science team, started and led by Xinlu Huang (Opendoor, Stanford PhD), supports our research and ML efforts. As we expand the biometric data and analytes we're able to ingest, we will continue expanding our capabilities to achieve state-of-the-art biological observability.