Data Operations Manager, Human Data

Anthropic•San Francisco, NY

3d•Hybrid

About The Position

As Data Operations Manager, you'll build and scale data operations across research teams working on frontier AI capabilities. You'll partner with researchers to design and execute data strategies, manage vendor relationships, and own the entire data pipeline from requirements to production. This role requires operational excellence combined with technical depth to understand what makes high-quality training data, but your focus will be on strategy and execution. The data operations you build will directly determine how well our models perform on critical capabilities—tool use accuracy, prompt injection robustness, long-horizon reasoning, and safety alignment. You'll work with world-class researchers advancing the frontier while building the operational infrastructure to scale these efforts. We're looking for someone who gets excited about the challenge of scaling quality across diverse research areas—someone who can understand nuanced technical requirements, build the right partnerships, and execute flawlessly. If you thrive at the intersection of operational excellence and cutting-edge AI research, we'd love to hear from you.

Requirements

Have 3+ years in operations, consulting, product management, or program management roles
Have exceptional project management skills with ability to handle multiple complex projects simultaneously
Have strong communication skills and can engage effectively with technical and non-technical stakeholders
Are familiar with how LLMs work or have strong interest in understanding AI training methodologies
Are highly organized and can navigate ambiguity effectively
Have experience with data analysis tools (SQL, Python, Tableau, spreadsheets, or similar)
Thrive in fast-paced research environments with shifting priorities
Are passionate about AI safety and understand the critical importance of high-quality data
Bachelor’s degree or an equivalent combination of education, training, and/or experience
A field relevant to the role as demonstrated through coursework, training, or professional experience

Nice To Haves

Experience with data collection, labeling, or annotation operations for AI/ML systems
Knowledge of RLHF, constitutional AI, or human-in-the-loop workflows
Background working with research teams at AI companies or research-oriented organizations
Experience managing vendor relationships or external contractors
Consulting background with experience translating complex requirements into deliverables
Track record of implementing process improvements or quality control systems at scale

Responsibilities

Own and execute data strategy for research teams advancing frontier AI capabilities across RLHF, safety, tool use, and agentic workflows
Drive strategic vendor partnerships and build scalable frameworks for technical data collection at scale
Design and implement operational systems that translate research requirements into high-quality data pipelines
Build evaluation frameworks and quality standards that ensure data meets the bar for training state-of-the-art AI systems
Lead cross-functional initiatives to optimize research velocity while maintaining rigorous quality standards
Proactively identify risks, bottlenecks, and opportunities to improve efficiency and effectiveness across data operations
Partner with senior research leaders to align data operations with model development roadmaps and strategic priorities