Head of Data Operations

About Us

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.

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We value in-person teamwork and believe the best ideas happen together. Our team is expected to be in the office five days a week in Palo Alto, CA, unless explicitly noted otherwise in the job description.

About the Role:

We are seeking a Head of Data Operations to lead the teams and partners responsible for data generation, annotation, evaluation, and RLHF (reinforcement learning from human feedback) across Hippocratic

AI’s healthcare agent products.

This leader will own the entire data operations lifecycle — from sourcing and labeling to model evaluation and feedback — ensuring precision, scalability, and alignment with our safety and ethics principles. You will manage internal teams, global contractors, and strategic vendors to deliver high-quality data pipelines that enable continual learning and improvement of our agentic systems.

Team & Vendor Leadership

• Build, lead, and scale a global data operations organization including full-time employees, contractors, and vendor partners.

• Define clear roles, quality standards, and performance metrics across all data functions (evaluation, labeling, RLHF, and generation).

• Partner with Legal, Compliance, and Security to ensure all global data work adheres to HIPAA and data privacy standards.

Data Program Management

• Oversee the design and execution of evaluation frameworks for LLMs and agentic behaviors — both automated and human-in-the-loop.

• Lead data labeling, synthesis, and annotation operations
  , ensuring medical accuracy, consistency, and context-rich quality.

• Manage large-scale RLHF pipelines — aligning training data with clinical and ethical objectives.

• Optimize throughput, cost, and quality across in-house teams and external vendors.

Process, Tooling, and Quality

• Partner with engineering and product to design and improve data operations infrastructure
  , including labeling tools, quality assurance systems, and task routing platforms.

• Implement robust QA processes and auditing frameworks to ensure data integrity and reliability.

• Drive continuous improvement in efficiency, consistency, and evaluator experience.

Cross-Functional Collaboration

• Work closely with Research, Model, and Product teams to define data needs and feedback loops.

• Collaborate with Clinical and Safety leaders to align annotation and evaluation standards with clinical guidelines.

• Provide strategic input into data strategy, metrics, and operational planning.

Must Have:

• 10+ years of experience in data operations, annotation, or model evaluation
  , with 5+ years in management or leadership roles.

• Proven success scaling data or RLHF operations across geographies and vendors.

• Strong program management and process optimization skills; experience managing distributed teams.

• Familiarity with LLM training and evaluation
  , RLHF, or human-in-the-loop systems.

• Deep respect for data ethics, privacy, and quality — ideally within healthcare, life sciences, or another regulated industry.

• Excellent communication and collaboration skills; able to navigate between technical, clinical, and operational stakeholders.

Nice-to-Have:

• Experience in medical or healthcare data annotation or clinical workflow modeling
  .

• Prior work building custom data pipelines or labeling platforms
  .

• Understanding of LLM fine-tuning, preference modeling, and evaluation metrics
  .

• Global vendor management experience with large-scale workforce operations.

*** Be aware of recruitment scams impersonating Hippocratic AI. All recruiting communication will come from  email addresses. We will never request payment or sensitive personal information during the hiring process. If anything