Senior Human-AI Collaboration Research Engineer, Education Labs
Description
Education Labs is a research-driven team with a product mandate: we study how AI transforms human capability development, and we build new product paradigms based on what we discover. As a Senior Product Research Engineer, you'll be the second technical builder on this small, mission-driven team—operating with research-level autonomy while shipping features that reach millions of users.
This role sits at the intersection of research exploration and product execution. You'll work alongside researchers studying the societal impacts of AI, while building and shipping features that help people develop skills—both in working with AI itself and in their broader capabilities. You'll have significant creative license to define what “good” looks like, exploring new interaction paradigms rather than optimizing existing patterns.
Our team believes that developing skill with AI is fundamental to human agency and flourishing in an AI-enabled world. We're building experiences that make users more capable, more thoughtful, and more empowered—not just more engaged. This means integrating skill development principles into product design, leveraging Claude itself as part of the capability-building journey, and measuring success by how users grow in their ability to work with AI and apply those skills to their own goals.
You'll be something of a one-person technical shop with full-stack ownership, prototyping new ideas, establishing technical direction, and shipping production-quality features. You'll need strong product instincts and clean interface design sensibilities, balanced with comfort in ambiguity and frontier thinking.
Responsibilities:
- Build and ship features that help users develop skills in working with AI and translate those skills into their own capability growth—measuring success by skill development and product mastery, not just engagement
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Architect and implement end-to-end prototypes (front-end and back-end) that test new interaction paradigms for skill development with AI, including novel uses of Claude as a skill-building partner
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Define technical direction and quality standards for capability-focused product work in a research context—you'll establish patterns others can follow
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Collaborate with researchers to translate insights about skill development and human-AI collaboration into shipped product experiences
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Work closely with product, design, and research teams across Anthropic to influence how skill development principles shape our broader product strategy
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Analyze product data and user behavior using quantitative and qualitative methods to understand how users develop skills with AI and what actually helps them become more capable
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Document and share your work through clear technical writing, prototypes, and presentations that influence thinking across the organization
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Elevate team craft through thoughtful code reviews, technical discussions, and knowledge sharing—helping others grow their skills
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Influence research priorities and team strategy while mentoring through technical leadership—establishing patterns, stakeholder coordination, reviewing code, and sharing expertise
Qualifications
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Strong full-stack engineering experience
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6+ years building and shipping web products, with deep expertise across the stack
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Strong front-end skills: TypeScript/JavaScript, React, HTML/CSS, with an eye for clean, intuitive interface design
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Solid back-end and data pipeline experience: Python, API design, data analysis infrastructure
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Track record of independently driving features from prototype to production quality
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Comfort working as a technical "one-person shop" with full ownership
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Deep conviction about human capability and agency
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Strong perspective on how technology should enhance human capabilities rather than diminish them
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Experience or genuine passion for skill development, human-computer interaction, developer tools, or products that help people become more capable
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Understanding that skill development isn't tutorials or onboarding flows—it's experiences that make users progressively more capable, curious, and empowered over time
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Interest in how people develop mastery of AI itself and how that translates to broader capability growth
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Skepticism of purely engagement-driven metrics; interest in measuring skill development and capability outcomes
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Research mindset with product execution skills
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Comfort with ambiguity and exploring undefined problem spaces—you define what good looks like
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Experience working in research contexts or highly exploratory product environments
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Ability to rapidly prototype new ideas, test them with users, and iterate toward production
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Strong instincts for product design and user experience, even without formal design training
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Excitement about frontier thinking and new paradigms, not just optimization
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Strategic thinking and focus
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Experience setting vision for product projects, defining roadmaps with clear milestones, and maintaining team focus in exploratory environments
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Ability to balance research exploration with concrete deliverables and timelines
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Strong sense of prioritization—knowing what to build now, what to defer, and what to cut
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Track record of translating ambiguous opportunities into actionable plans
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Technical leadership and communication
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Experience providing technical direction, particularly in small or early-stage teams
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Ability to work effectively alongside researchers, translating between research insights and product implementation
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Strong written and verbal communication—you make complex technical and conceptual ideas accessible
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Track record of elevating team output through code quality, documentation, and knowledge sharing
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Experience in developer tools, creative tools, learning platforms, or other products where user skill development and mastery matter more than time-on-site
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Background in learning sciences, cognitive science, HCI, skill acquisition research, or educational psychology (formal or self-directed)
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Experience with experimentation frameworks, A/B testing, or analytics that measure capability development in production
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Previous experience in research labs, frontier tech companies, or startups with high autonomy and ambiguity
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Published writing, talks, or open-source work on skill development, human-AI interaction, or product philosophy
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Experience building AI-native product experiences or working with LLMs in production contexts