AI Lead - Product Engineering (Healthcare)

Location: US - Remote

Company

hirify.global is building an AI-powered health platform that combines lab testing, medical imaging, longitudinal data, and clinical guidance to help members understand and improve their health.

What you will do

• Define and lead the AI infrastructure and product engineering roadmap.
• Apply generative AI, knowledge graphs, and emerging research techniques to healthcare challenges.
• Mentor and guide a multidisciplinary team of researchers, data scientists, and engineers.
• Ensure AI applications are innovative, trustworthy, sustainable, and compliant with applicable regulations.
• Partner with senior leadership, product teams, clinical experts, regulatory affairs, and marketing to align AI strategy with business and clinical priorities.
• Communicate complex AI concepts, research insights, and strategic direction to technical and non-technical stakeholders.

Requirements

• 10+ years of experience in data science, deep learning, expert systems, generative AI, and machine learning.
• Experience as a technical lead managing researchers, data scientists, or engineers.
• Strong analytical, problem-solving, innovation, and strategic planning skills.
• Experience building and leading multidisciplinary teams and communicating complex AI concepts to executives and other non-technical stakeholders.
• Understanding of responsible AI, HIPAA, and relevant data privacy regulations.
• Authorization to work in the US or Canada is requested in the application.

Nice to have

• Startup experience, particularly as a founder or early engineering hire.
• Experience with health technologies such as Oura, Whoop, Apple Watch, or continuous glucose monitors.
• Experience integrating imaging, genomics, text, and sensor data into multimodal AI pipelines.
• Experience deploying AI solutions on AWS, Azure, Google Cloud, or edge devices.

Culture & Benefits

• Flexible working hours and a remote work environment.
• Competitive salary and benefits package.
• Culture focused on member-first outcomes, rapid execution, ownership, collaboration, and integrity.
• Emphasis on clinical precision, responsible AI, and accuracy in health data.
• Commitment to diversity, inclusion, and equal employment opportunity.