Research Operations and Strategy Lead

About Anthropic

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About The Role: Research Operations and Strategy Lead

As the Research Operations and Strategy Lead, you'll build and scale data operations that advance Claude's coding and cybersecurity capabilities. You'll partner with research teams to design and execute data strategies, manage vendor relationships, and own the entire data pipeline from requirements to production. This is a zero-to-one role requiring technical depth to understand what makes high-quality training data, but your focus will be on strategy and execution rather than hands-on engineering. Think technical founder who evolved from writing code to building the business.

About The Impact

The data strategies and operations you build will directly determine how well our models can write code, understand software systems, and identify security vulnerabilities. You'll work with world-class researchers on frontier AI capabilities while building the operational infrastructure to scale these efforts.

We're looking for someone who gets excited about the challenge of scaling quality - someone who can think strategically about data needs, build the right partnerships, and execute flawlessly. If you thrive at the intersection of technical depth and operational excellence, we'd love to hear from you.

Responsibilities

• Develop and execute data strategies for coding capabilities, cybersecurity evaluations, and agentic AI research
• Partner with research leaders to translate technical requirements into operational frameworks
• Build data collection and evaluation systems through internal tools, vendor partnerships, and new approaches
• Identify, evaluate, and manage specialized contractors and vendors for technical data collection
• Implement quality control processes to ensure data meets training requirements
• Manage multiple complex projects simultaneously, balancing technical needs with delivery timelines
• Track metrics and communicate progress to stakeholders

You May Be a Good Fit If You

• Have 3+ years in technical operations, product management, or entrepreneurial experience building from zero to scale
• Have strong technical foundations - proficiency in Python and understanding of ML workflows and evaluation frameworks
• Have strong communication skills and can effectively engage with both technical and non-technical stakeholders, both internal and external parties
• Are familiar with how LLMs work and could describe how models like Claude are trained
• Are highly organized and can manage multiple parallel workstreams effectively
• Have a high threshold for navigating ambiguity and can balance setting strategic priorities with rapid, high-quality execution
• Thrive in fast-paced research environments with shifting priorities and novel technical challenges
• Are passionate about AI safety and understand the critical importance of high-quality data in building beneficial AI systems

Strong Candidates May Also Have

• Experience at companies training AI models, agents, or creating AI training data, evaluations, or environments
• Knowledge of AI safety research methodologies and evaluation frameworks
• Experience with RLHF or similar human-in-the-loop training methods
• Domain expertise in software engineering or cybersecurity
• Track record of building and scaling operations teams

Logistics

• Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time.
• Visa sponsorship: We do sponsor visas!

Key skills/competency

• Data Strategy
• Operations Management
• Vendor Management
• Project Management
• Quality Control
• AI Safety
• Machine Learning Workflows
• Python Programming
• LLMs Understanding
• Cybersecurity Data