Develop Health

Security Engineer

• Own infrastructure and end-to-end security; report to CTO; work on-site in Palo Alto/Menlo Park at least 3 days/week.;Take full ownership of GCP stack (Terraform + GKE); tighten monitoring, performance, and networking.;Elevate developer experience in GitHub Actions—speed up pipelines, streamline environments, and automate common tasks.;Research, evaluate, and roll out AI‑powered security tooling (vulnerability discovery, code‑review assistants, policy‑as‑code scanners).;Assume day‑to‑day responsibility for SOC 2 & HIPAA technical controls and drive HITRUST certification.;Continuously probe for weaknesses—perform internal security reviews, harden endpoints, and champion best practices.;Architect multi‑region, highly available platform; define and track SLOs/SLAs; introduce new controls and automate patching; mentor future hires.

Founding Platform and Security Engineer

Full-stack Engineer

• Build intuitive and impactful user interfaces that allow healthcare providers to easily leverage state-of-the-art AI advancements.
• Integrate advanced AI solutions, including the latest LLMs, into healthcare workflows through seamless EHR integrations.
• Work closely with our AI team to improve our models, systematically gathering product feedback and data insights from users.
• Collaborate directly with other engineers, clinical leaders, and the CTO to ensure our product aligns with real-world clinical needs and workflows.
• Shape how healthcare providers interact with advanced AI tools to enable faster and more informed clinical decisions.

Product Engineer

AI Engineer

• Build and curate datasets for training and evaluating our AI models.
• Build and maintain robust evaluation pipelines to rigorously measure and continuously improve AI performance.
• Prompt, evaluate, and iterate on LLM workflows—retrieval, agent logic, tool use—to ensure they lead the industry in accuracy and reliability.
• Own the deployment lifecycle—designing APIs, integrating model inference into our Python‑based backend, instrumenting observability, and monitoring performance in production.
• Stay deeply connected to the latest developments in AI research and rapidly integrate relevant advancements.
• Collaborate directly with product engineers, clinical leaders, and the CTO to ensure our AI directly meets clinical needs.
• Exercise significant autonomy to choose projects and drive them from concept to completion.