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 Claude Platform ships fast, and every launch lands better when the field can understand it, demo it, and teach it.
You'll own platform enablement end to end: the demos, hands-on labs, and technical curriculum that let Anthropic's go-to-market teams showcase the Claude Developer Platform with confidence, whether they're building on Anthropic's first-party API or through Bedrock, Vertex, and Foundry. You'll join roadmap and launch planning with the product team before features ship, so the field has what it needs on day one.
You're an engineer who teaches. You've shipped products to users. You know the difference between a demo that raises awareness and one that creates champions. And you get as much energy from watching a seller nail your lab as from building it yourself.
Turn launches into field-ready content: Translate new platform capabilities (API, tool use and MCP, Agent SDK, memory and skills) into demos, labs, and quick-reference guides within days of release, and build compelling demo scenarios across industries and developer personas
Deliver training that sticks: Run Claude Platform training for technical onboarding and ongoing enablement programs, delivering hands-on sessions wherever the field gathers, from a 12-person lab to a 100-person field-readiness day
Coach the field: Coach technical sellers on demo delivery through practice sessions and office hours
Scale beyond the live session: Develop self-service resources and experimental tools so the field can learn without you in the room, and contribute to the tooling that scales enablement, including demo environments, content-freshness automation, and self-service infrastructure
Close the loop with product: Stress-test new platform features before launch, then bring field signal back to product and product marketing on where sellers get stuck and what content would unlock the next deal
Measure what lands: Track content usage and session feedback so you know what is working and what to retire
Experience in a customer-facing technical role, such as solutions architecture, sales engineering, developer relations, or technical enablement
Experience writing production-quality code and building technical demos
Hands-on experience building with LLM APIs and agents, including tool use, MCP, or agent frameworks, beyond prompting alone
Experience using AI coding tools as part of your daily engineering work
Experience delivering live technical training or talks to both technical and non-technical audiences
Experience partnering directly with sales, solutions engineering, or other go-to-market teams
A portfolio you can show us: labs, courses, talks, or repos you built yourself
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 cloud providers such as Amazon Bedrock, Google Vertex AI, or Microsoft Foundry
Experience as a technical founder, early startup employee, or 0-to-1 operator who has taken an idea to product-market fit
Public speaking, conference presentations, or community-facing developer advocacy
Experience building enablement tooling, such as demo environments, content-freshness automation, or self-service infrastructure
Deep enthusiasm for AI and genuine care about building it responsibly
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.
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.