Everlywell is a digital health company pioneering the next generation of biomarker intelligence—combining AI-powered technology with human insight to deliver personalized, actionable health answers. We transform complex biomarker data into life-changing insights—seamlessly integrating advanced diagnostics, virtual care, and patient engagement to reshape how and where health happens.
Over the past decade, Everlywell has delivered close to 1 billion personalized health insights, transforming care for 60 million people and powering hundreds of enterprise partners. In 2024 alone, an estimated 1 in 86 U.S. households received an Everlywell test, solidifying our spot as the #1 at-home testing brand in the country. And we’re just getting started. Fueled by AI and built for scale, we’re breaking down barriers, closing care gaps, and unlocking a more connected healthcare experience that is smarter, faster, and more personalized.
Everlywell is entering a new era—one where data and AI will shape the future of diagnostics, consumer health, and enterprise health plan solutions. As the Director of AI and Data Engineering, you will lead the vision, strategy, and execution of our AI and data platform capabilities. This role will drive the foundation and innovation layer that powers predictive insights, personalized health journeys, and next-gen diagnostics intelligence—at scale.
You will be both a strategic architect and technical leader, managing a small, high-impact team while collaborating cross-functionally to make data a transformative, competitive advantage.
AI and Data Strategy & ArchitectureDefine and execute a comprehensive strategy for AI and data infrastructure, focused on scalability, reliability, and business impact.Drive innovation in machine learning (ML) and large language model (LLM)-powered applications, from concept to production.Evaluate and implement emerging AI techniques (e.g., retrieval-augmented generation, agentic workflows, multimodal models) aligned to our diagnostics and consumer product roadmap.Technical Leadership:Lead architectural decisions across data warehousing, pipelines, model deployment, and real-time inference systems.Design and evolve our data ecosystem (including structured lab/test data, behavioral data, partner integrations) to serve both AI initiatives and enterprise analytics needs.Oversee development and integration of ML models into customer-facing features, health recommendations, and operational tooling.