Head of Technical Training

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.

The world’s engineers are hungry to learn how to get the most out of Claude. At Anthropic, technical instruction is already happening everywhere: our Applied AI and Forward Deployed Engineering teams are teaching customers and partners, and engineers across the company are helping others learn to build with Claude. Today, that instruction is a shared responsibility, delivered alongside people’s primary roles. As demand grows, we need to turn that distributed expertise into a world-class technical instruction function.

You will build that function.

You will be the first person at Anthropic whose full-time job is technical instruction. You’ll spend your first year primarily in the room, teaching engineers, architects, and other technical practitioners, and build the people, standards, and systems that allow Anthropic’s technical instruction to scale far beyond the people we directly employ.

This is a player-coach role. You’ll lead sessions yourself, manage a bench of technical instructors, set the bar for what “ready to teach” means, and certify others to teach to that bar both inside and outside Anthropic. You’ll have real ownership: you’ll decide who is cleared to teach in Anthropic’s technical programs.

You’re an engineer who teaches and a teacher who has led other teachers. You can build an agent live in front of a skeptical engineer, diagnose what isn’t working in a technical lab, and make the material better. You can also watch an experienced instructor teach, identify what’s missing, and tell them their session isn’t ready yet, then coach them to get there.

• →Lead from the front: Deliver hands-on technical instruction across Anthropic’s onboarding and residency programs, from 12-person labs to 100-person field-readiness days. Set the tone for technical instruction by teaching regularly and modeling what excellent delivery looks like.
• →Build the instructor bench: Hire, onboard, manage, and develop technical instructors. Run the hiring loop, establish clear performance expectations, and make renewal and conversion decisions against criteria you define.
• →Set the quality bar: Define what excellent technical instruction looks like at Anthropic. Create and maintain the observation rubric, dry-run protocol, and cleared-to-teach process that every instructor-led technical session must meet.
• →Scale through certification: Design and run train-the-trainer programs for internal experts, contract instructors, and facilitators from our training partners. Assess instructors against Anthropic’s technical delivery standards and certify those who meet the bar, enabling instruction to scale beyond our employees.
• →Turn expertise into great instruction: Partner with Technical Enablement Leads to transform technical content into sessions, labs, and exercises that work in a live room. Bring back what you learn from teaching to continuously improve the content.
• →Enable programs without owning them: Partner with our onboarding and Training & Certification teams to staff programs with cleared instructors. Own the quality of instruction within those programs, even when the broader program sits elsewhere.
• →Measure and improve: Establish meaningful measures of learner outcomes and instructor quality. Review results at the session and instructor level, identify where instruction is falling short, and act on what you learn.

• 8+ years of relevant professional experience across software engineering, solutions engineering, developer advocacy, technical education, or related technical roles.
• 4+ years of hands-on technical instruction: You have taught engineers in live, hands-on settings, across different audience sizes and levels of technical depth. You know how to make a technical concept click in a room and how to adapt when it doesn’t.
• Production engineering experience: You have written and shipped production code and can engage credibly with experienced engineers on architecture, implementation, debugging, and technical tradeoffs.
• Recent hands-on AI development: Within the past three years, you have built or debugged applications using LLM APIs, agent frameworks, tool use, MCP, or similar technologies. You are comfortable getting hands-on with unfamiliar technical problems rather than teaching only from prepared material.
• People leadership: You have managed instructors, trainers, developer advocates, solutions engineers, or similar technical practitioners, including hiring, coaching, performance management, and development. You have continued teaching or delivering technical content while managing others.
• Instructor development: You have designed or run a train-the-trainer program, instructor certification process, observation framework, or comparable system for evaluating and improving instructor quality.
• Location: Based in San Francisco or willing to relocate. This role requires being in the SF office whenever an instructor-led program is in session, typically 3–4 days per week.

• A portfolio you can show us: sessions, labs, or courses you built and taught, and a rubric, certification, or TTT program you designed for others
• Experience building an instruction or developer-education function from scratch
• Experience managing a contractor or vendor-supplied instructor bench, or certifying instructors across regions from recordings or through trained observers
• Experience with Claude Code, or a comparable agentic coding tool, as core infrastructure in your daily work
• Experience building on the Claude Developer Platform through Amazon Bedrock, Google Vertex AI, or Microsoft Foundry
• Public speaking, conference workshops, or community-facing developer advocacy
• Deep enthusiasm for AI and genuine care about building it responsibly

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

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.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

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.

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.