Data Operations Manager, Knowledge

Anthropic Anthropic · AI Frontier · AI Research & Engineering

Lead human data collection initiatives to power advanced AI capabilities, focusing on AI safety and capability research. Design and build novel data collection systems and evaluation frameworks, translating research into scalable data systems. This is a 0-to-1 role requiring operational excellence at the intersection of AI research and execution.

What you'd actually do

  1. Lead comprehensive data strategies for Claude Skills, Safety evaluations, and frontier capability assessment that directly impact model performance and safety
  2. Design and build novel data collection systems and evaluation frameworks that enable rigorous measurement of AI capabilities and safety properties
  3. Partner with researchers, engineers, and product teams to scope complex projects, resolve technical blockers, and ensure seamless integration with training pipelines
  4. Build and manage relationships with specialized contractors and vendors for highly technical data collection requirements
  5. Implement robust quality control and verification processes to ensure data usability for training state-of-the-art AI systems

Skills

Required

  • 5+ years of experience in technical operations, product management, or similar roles
  • Entrepreneurial experience as a technical founder, early-stage startup operator, or in similar 0-to-1 leadership roles
  • Strong technical intuition for what makes high-quality training data for advanced AI systems
  • Experience with AI systems, large language models, or evaluation frameworks
  • Exceptional project management skills
  • Ability to coordinate complex technical initiatives across multiple teams
  • Comfortable operating in highly ambiguous environments
  • Strong product mindset
  • Thrive in fast-paced research environments

Nice to have

  • Experience building or working with AI agents, evaluation systems, or advanced AI safety methodologies
  • Background in designing and implementing evaluation systems or human-in-the-loop workflows for large language models
  • Experience with agentic AI systems, computer use capabilities, or advanced reasoning assistance tools
  • Knowledge of AI safety evaluation, red teaming, constitutional AI, or related AI safety methodologies
  • Background in human-computer interaction (HCI), user experience design
  • Experience in high-growth startup environments
  • Background collaborating with AI researchers or experience in research-oriented organizations
  • Technical expertise in areas like data pipelines, evaluation frameworks

What the JD emphasized

  • build complex systems from the ground up
  • built both processes and products
  • define both the "what" and the "how" from scratch

Other signals

  • data collection
  • AI safety
  • frontier research
  • scalable execution
  • data as the product