Head of Engineering

Hippocratic AI has developed a safety-focused Large Language Model (LLM) for healthcare. The company believes that a safe LLM can dramatically improve healthcare accessibility and health outcomes in the world by bringing deep healthcare expertise to every human. No other technology has the potential to have this level of global impact on health. 

• Innovative Mission: We are developing a safe, healthcare-focused large language model (LLM) designed to revolutionize health outcomes on a global scale.

• Visionary Leadership: Hippocratic AI was co-founded by CEO Munjal Shah, alongside a group of physicians, hospital administrators, healthcare professionals, and artificial intelligence researchers from leading institutions, including El Camino Health, Johns Hopkins, Stanford, Microsoft, Google, and NVIDIA.

• Strategic Investors: We have raised a total of $278 million in funding, backed by top investors such as Andreessen Horowitz, General Catalyst, Kleiner Perkins, NVIDIA’s NVentures, Premji Invest, SV Angel, and six health systems.

• World-Class Team: Our team is composed of leading experts in healthcare and artificial intelligence, ensuring our technology is safe, effective, and capable of delivering meaningful improvements to healthcare delivery and outcomes.

We are seeking a Head of Engineering to lead and oversee the design, development, and scaling of our core technology infrastructure and software systems. This is a pivotal role in ensuring that our engineering teams deliver scalable, high-performing, and secure solutions that meet evolving business needs. The ideal candidate is a strategic leader with deep technical expertise and a passion for fostering collaboration and innovation across teams.

For more information, visit www.HippocraticAI.com.

We value in-person teamwork and believe the best ideas happen together. This role is expected to be in the office five days a week in Palo Alto, CA.

• Develop and execute the overall engineering strategy, aligning it with the company’s business objectives.

• Lead and mentor engineering teams across software development, infrastructure, and product engineering.

• Foster a culture of innovation, continuous improvement, and collaboration within and across teams.

• Oversee the design, development, and delivery of scalable and robust software solutions.

• Ensure the architecture supports future growth, scalability, security, and performance.

• Work closely with product management to translate business needs into technical requirements and engineering plans.

• Ensure high availability, performance, and reliability of all engineering systems and infrastructure.

• Drive improvements to CI/CD pipelines, automation, and development processes.

• Collaborate with DevOps and cloud engineering teams to manage cloud infrastructure, ensuring cost-efficiency and resilience.

• Partner with research, product, and business teams to support product innovation and new feature development.

• Act as a bridge between technical and non-technical stakeholders, effectively communicating key concepts and project progress.

• Represent engineering in executive meetings and provide strategic input on company initiatives.

• Stay ahead of emerging trends, technologies, and methodologies to keep the organization competitive.

• Introduce best practices and modern engineering processes to enhance team productivity and product quality.

• Extensive experience in leading and scaling engineering teams in a fast-paced, innovative environment.

• Strong software development background, with expertise in modern languages and frameworks (e.g., Python, Java, Go, or similar).

• Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and distributed systems.

• Experience with modern DevOps tools, CI/CD pipelines, and Infrastructure as Code (e.g., Terraform, Kubernetes).

• Knowledge of software architecture, microservices, and system design best practices.

• Experience working with AI/ML systems and tools such as TensorFlow, PyTorch, or Hugging Face.

• Understanding of LLM lifecycle management, fine-tuning, and serving models in production.

• Familiarity with vector databases, embedding models, and retrieval-augmented generation (RAG) architectures.

• Hands-on knowledge of data pipelines, model monitoring, and performance optimization techniques for AI applications.

• Proven track record of managing and mentoring engineering teams to achieve technical and business excellence.

• Strong decision-making and problem-solving skills, with a focus on delivering results.

• Excellent communication skills, with the ability to present complex ideas to stakeholders across different disciplines.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience).

• 8+ years of experience in engineering, with at least 3 years in a senior leadership role.