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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:

You’ll be the architect of Anthropic’s non-technical curriculum, designing structured learning pathways that guide users from basic AI understanding to advanced proficiency. You’ll work closely with our research, societal impacts, and education teams to develop comprehensive courses, learning modules, and educational frameworks that serve all kinds of audiences from students to business professionals. Your work will focus on creating cohesive, pedagogically sound learning experiences for both Claude apps and general AI fluency for specific audiences. You’ll design multi-format learning paths that include videos, exercises, quizzes, and more.

Core responsibilities:

    • Own the complete curriculum development lifecycle for non-technical courses from initial concept through content creation, assessment design, launch, and ongoing iteration
    • Design and develop comprehensive AI fluency curricula for different audience segments
    • Create structured learning pathways with clear progression from foundational concepts to advanced applications
    • Build and maintain strategic partnerships with educational institutions, subject matter experts, and industry leaders to co-develop and validate curriculum effectiveness
    • Develop assessment frameworks and learning measurement systems to track comprehension and skill development
    • Manage and direct external agencies and contractors for video production, graphic design, and multimedia content creation while maintaining quality standards and brand alignment
    • Report on learning outcomes and iterate curriculum based on user feedback and educational effectiveness data
    • Represent Anthropic’s educational mission in external partnerships and industry forums, maintaining strong relationships with key stakeholders

You may be a good fit if you:

    • Have 4+ years experience in curriculum development or instructional design for diverse audiences with demonstrated ability to own projects end-to-end
    • Experience creating comprehensive, multi-modal learning experiences that explain technical concepts to non-technical users across written and video formats
    • Deep understanding of pedagogical principles and learning theory, particularly for adult learners and professional development
    • Strong alignment with Anthropic’s mission and values around responsible AI development and beneficial technology deployment
    • Possess exceptional project management skills with experience managing complex, multi-stakeholder educational initiatives
    • Confidence managing both strategic curriculum planning and detailed content development
    • Are passionate about creating systematic approaches to AI education that serve diverse learning needs

Strong candidates may also have:

    • Experience developing courses or curricula for emerging technologies or AI-related topics
    • Background in educational technology, learning management systems, or online course development
    • Experience with educational measurement, assessment design, and learning analytics
    • Previous work in higher education, corporate training, or professional development programs
    • Experience co-creating curriculum with partners and representing organizations in external relationships

 

The expected salary range for this position is:

Annual Salary:

$160,000 – $255,000 USD

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. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren’t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you’re interested in this work. We think AI systems like the ones we’re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

How we’re different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We’re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

About Organization

We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale.

Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.

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