Head of AI Engineering

Job Title: Head of AI Engineering

Location: Fully Remote (Work Pacific Time Zone)

Salary: $260K - $400K + Equity

Skills: 7+ years, Series A/B experience, LLM Engineer, Senior Leader/Division Leader, GenAI, LLMs, full lifecycle of AI Infrastructure


About Company / Opportunity:

An early-stage AI healthcare technology startup is seeking a hands-on Head of AI Engineering to lead the buildout and scaling of cutting-edge agentic AI systems. This role offers a unique opportunity to shape the future of healthcare automation by developing AI agents that improve medical workflows and operational efficiency. You will work closely with leadership in a fast-paced environment to build and mentor a top-tier engineering team.


Responsibilities:

  • Architect and implement AI systems powered by LLMs and GenAI frameworks
  • Lead and grow the AI engineering team, fostering a culture of ownership and innovation
  • Collaborate cross-functionally with product and leadership to define technical strategy
  • Oversee full lifecycle of AI infrastructure including development, deployment, and monitoring
  • Participate hands-on in coding, reviewing, and scaling AI products


Must-Have Skills:

  1. Proven leadership managing and scaling engineering teams at startups or mid-sized AI companies
  2. Deep hands-on experience with AI systems and LLM implementation
  3. Expertise in GenAI frameworks and production-grade AI infrastructure
  4. Proficiency in Node.js, TypeScript, and front-end frameworks such as React
  5. Experience building engineering practices from scratch in early-stage or Series A/B startups
  6. Ability to thrive in a fast-moving startup environment with strong execution focus
  7. Excellent communication skills for technical and non-technical collaboration


Nice to Have Skills:

  1. Background as a founding engineer, Head of Engineering, or AI leader at AI-first or healthcare startups
  2. Experience with healthcare data, clinical workflows, or healthcare AI applications
  3. Hands-on experience with Python, Kubernetes, Docker, and cloud platforms (AWS, GCP, Azure)
  4. Contributions to open-source AI projects or AI community involvement