AI Fluency Education Lead

Posted 19 Hours Ago
Be an Early Applicant
2 Locations
In-Office
270K-365K Annually
Senior level
Artificial Intelligence • Natural Language Processing • Generative AI
The Role
Own and build a modular, model-agnostic AI fluency curriculum for public audiences: create multimedia content, design AI-assisted production pipelines, prototype novel learning formats, partner with external institutions, and measure real learning outcomes to iterate and scale.
Summary Generated by Built In
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

Anthropic is seeking an AI Fluency Education Lead to create courses and content that teach people how AI works and how to work well with AI. Most people right now pick up AI wherever they happen to find it: a prompt from a coworker, a video promising ten hacks, or a screenshot from LinkedIn. It’s hard to discern which tidbits are short term tactics and what skills will be enduring. AI Fluency is our work to close that gap: teaching how AI actually works, and how to work well alongside it, so people can make their own decisions and judgements with AI instead of copying someone else’s. Note that this does not cover product training. We recognize that most people do not use a single tool or single model, so  AI Fluency is deliberately model agnostic. We teach durable mindsets and understandings that help someone use AI well and safely, no matter what system is in front of them. 

Much of this role is about creation: writing, filming, prototyping, and publishing. It’s also about building the systems that let that work multiply and reach the right audiences. We can't teach every audience ourselves, so you'd design a modular library — short videos, exercises, frameworks, one-pagers, all free and openly licensed — along with the AI-assisted pipelines that remix and assemble those pieces into something specific for a given learner. You will also work with other teams to decide which audiences we go after, which topics we prioritize, and which formats we pursue. You may also invent formats that don't exist yet, because most AI education still looks like an online course from 2015 and we don't think the subject and the medium should be that far apart.

You would work closely with a sister group on the education team that researches what fluency means and how to measure it. You’re the person who takes that and turns it into something someone can actually learn from.



Key responsibilities

  • Own the curriculum for general-public AI fluency end to end — the roadmap, the sequencing, the quality bar, and the call on what we teach and what we deliberately leave out.

  • Curate and create the AI fluency material itself — curricula, courses, videos, essays, exercises, interactive lessons — and set the quality bar for any partner content creation engagements

  • Build AI-assisted production pipelines so the distance from an idea to a published piece keeps getting shorter while the quality keeps going up

  • Turn research frameworks into material that resonates for people whose jobs look nothing like ours: nurses, teachers, small business owners, policymakers, community leaders, and so on

  • Learn from and co-create with outside institutions, such as educators, public-sector organizations, and community groups

  • Prototype learning formats that only work with AI in the loop — personalized paths, conversational practice, assessment that adapts to the learner — and get rough versions in front of real people in days rather than quarters

  • Measure whether the teaching worked — completion is not comprehension, and comprehension is not changed behavior. Define what learning actually looks like for this audience and instrument for it.


You may be a good fit if you have

  • Deep experience designing content and curricula for adult learners at significant scale, with real taste for what makes learning stick when you’re not in the room. 

  • Exceptional writing for general audiences, and specifically the knack for turning a technical idea into a mental model that's accurate and also intuitive to novices and those who have never seen it before

  • Experience making multimedia learning content end to end — scripts, video, interactive — and working with agencies and partners to deliver on multiple projects in short deadlines

  • A working practice of using Claude and other LLMs as infrastructure in your own production

  • Enough technical comfort to build light tooling and automations yourself; this isn't an engineering role, but you shouldn't be intimidated by adding to the pipeline that produces your work

  • Experience-derived opinions about pedagogy you'll argue for, and the willingness to drop them when the data says otherwise

  • Genuine satisfaction in making things other people teach, such as a teacher taking your material, changing it for their audience, and delivering education without your oversight

  • Comfort in a fast-moving environment where you're building the process as you go

You don't need a background in AI or a degree in education, but you do need to have made people fluent in something before at scale.


Strong candidates may also have 

  • Built an education program or content function from nothing

  • Experience in public education, civic technology, or policy communication.

  • A background in AI/ML education, learning science, cognitive science, or behavioral research

  • Experience co-creating content with outside institutions and partners, not only with vendors and production agencies

  • Experience building AI-augmented content pipelines

The annual compensation range for this role is listed below. 

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary:
$270,000$365,000 USD
Logistics

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.

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.

Come work with us!

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.

Skills Required

  • Bachelor's degree or equivalent combination of education, training, and/or experience
  • Deep experience designing content and curricula for adult learners at scale
  • Exceptional writing for general audiences, turning technical ideas into intuitive mental models
  • Experience creating multimedia learning content end-to-end (scripts, video, interactive) and managing production partners
  • Working practice of using Claude and other large language models as infrastructure
  • Technical comfort building light tooling and automations for content pipelines
  • Experience turning research frameworks into teachable material for diverse nontechnical audiences
  • Experience measuring learning outcomes and instrumenting assessments that reflect comprehension and behavior change
  • Comfort working in a fast-moving environment and building processes iteratively
  • Experience making people fluent in a subject at scale (demonstrable track record)
  • Built an education program or content function from scratch
  • Experience in public education, civic technology, policy communication, or learning science/cognitive science research
  • Experience co-creating content with outside institutions and partners (not just vendors)
  • Experience building AI-augmented content pipelines

Anthropic Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Anthropic and has not been reviewed or approved by Anthropic.

  • Strong & Reliable Incentives Pay is positioned as top-of-market for many technical roles through a mix of high base pay, equity, and occasional bonuses/signing incentives. Benefits like substantial monthly stipends and employer-paid protections further strengthen perceived total rewards.
  • Healthcare Strength Healthcare is described as comprehensive across medical, dental, and vision, with additional mental-health support. Coverage is framed as robust for employees and dependents, which can materially increase the value of the overall package.
  • Parental & Family Support Paid parental leave is described as notably generous, alongside fertility coverage and other family-oriented supports. These elements broaden the rewards package beyond cash compensation and can improve retention for caregivers.

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The Company
HQ: San Francisco, California
2,500 Employees

What We Do

Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.

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