Staff Software Engineer, Education

Posted 8 Days Ago
Be an Early Applicant
2 Locations
In-Office
320K-405K Annually
Senior level
Artificial Intelligence • Natural Language Processing • Generative AI
The Role
Lead design and implementation of an AI-native education platform: authentication/SSO, learner data models, content delivery, credentialing, adaptive assessments, and AI-augmented pipelines. Own technical vision, integrate with security/infrastructure/data teams, and build tooling so non-engineers can configure educational experiences at 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 a Senior Full Stack Engineer to help build the technical foundation for how Anthropic educates customers and enterprises at scale, and to shape what that even means when AI is the delivery mechanism, not just the subject being taught.

Your work will define how millions of people experience learning about Claude: how content is served and adapted in real time, how assessments respond to what a learner actually understands, how credentialing systems verify genuine competence rather than course completion, and how the entire platform evolves as fast as the product it teaches. You'll build the infrastructure that makes AI-native education real — not as a concept, but as a working system that people interact with every day.

You’ll own the technical vision for our AI-driven educational experience: the platform layer, enterprise readiness features, the data architecture, the AI-augmented pipelines, the integrations, and the delivery systems. You'll work with a handful of highly technical educational collaborators to own the technical vision and execution for how Anthropic’s education team delivers educational experiences at scale, and you'll build the AI-augmented pipelines and platform capabilities that let a small team of educators operate with reach and responsiveness that would otherwise require an organization ten times larger.

This is an engineering role for someone who genuinely cares about how people learn. You'll make platform decisions that are deeply educational, and you need the judgment to make those decisions well, not just implement someone else's spec. You'll interface closely with Anthropic's security, infrastructure, and data teams, and you'll partner with trainers and educators on the GTM, devrel, and education teams who will be your primary stakeholders.

Responsibilities
  • Architect and own Anthropic’s enterprise ready education platform and infrastructure — authentication/SSO, learner data models, content delivery, credentialing, and progress tracking — designed for scale, AI-forward features, and reliability from day one

  • Own the technical vision for how Anthropic delivers AI-driven educational experiences and shaping what's possible, not just building what's requested. You’ll determine what to build, what to extend, and what to replace as needs evolve

  • Build AI-augmented pipelines for content generation, real-time adaptation, assessment delivery, and quality assurance — working closely with the education team to understand what these systems need to do pedagogically

  • Design platform capabilities that enable genuinely new kinds of empowering learning experiences — adaptive paths, competency-based progression, AI-evaluated demonstrations of skill — not just digital versions of traditional courses

  • Interface with Anthropic's security, infrastructure, and data teams to ensure education systems meet organizational standards and integrate cleanly with existing architecture

  • Build platform abstractions that let non-engineers on the team configure, extend, and experiment with educational experiences without engineering bottlenecks

  • Make product-level decisions about how the platform works — you're shaping what the learning experience is, not just serving it

You may be a good fit if you have
  • 7+ years of software engineering experience, with demonstrated ability to take a platform from zero to production at scale

  • Genuine passion for education — you think about how people learn, you have opinions about what educational technology should look like in an AI-native world, and you want to build it

  • A strong eye for quality educational content, with a sense of the complex systems that produce it

  • Full-stack engineering skills with particular strength in backend systems: databases, APIs, authentication, reliability, and infrastructure

  • Experience building and operating platforms that serve many concurrent users reliably

  • Comfort with ambiguity and ownership: you'll need to translate pedagogical intent into technical architecture without heavy specification

  • Experience interfacing with security and infrastructure teams to meet organizational requirements while maintaining development velocity

  • A working practice of using AI tools in your own engineering workflows — and genuine curiosity about how AI fundamentally changes what educational platforms can be

Strong candidates may also have
  • Experience building or significantly contributing to learning platforms, credentialing systems, or educational technology products

  • Background in or exposure to learning science, instructional design, or educational research

  • Experience with SSO/identity (SAML, OAuth), badging standards (Open Badges), or LTI integrations

  • Familiarity with building systems that incorporate LLM capabilities as core infrastructure

  • Prior work at a high-growth company where you built platform infrastructure that other teams depended on

  • Experience designing systems that non-technical users configure and operate

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:
$320,000$405,000 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

  • 7+ years of software engineering experience
  • Bachelor's degree or equivalent combination of education, training, and/or experience
  • Full-stack engineering skills with strength in backend systems: databases, APIs, authentication, reliability, and infrastructure
  • Experience taking a platform from zero to production at scale and operating platforms serving many concurrent users reliably
  • Experience interfacing with security and infrastructure teams to meet organizational requirements
  • Working practice of using AI tools in engineering workflows and familiarity with AI-augmented pipelines
  • Ability to translate pedagogical intent into technical architecture and exercise product-level judgment
  • Experience building learning platforms, credentialing systems, or educational technology products
  • Background or exposure to learning science, instructional design, or educational research
  • Experience with SSO/identity (SAML, OAuth), badging standards (Open Badges), or LTI integrations
  • Familiarity building systems that incorporate LLM capabilities as core infrastructure
  • Prior work at a high-growth company building platform infrastructure used by other teams
  • Experience designing systems non-technical users can configure and operate

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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