Applied AI Architect, Beneficial Deployments (Life Sciences Community & Enablement)

Posted Yesterday
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2 Locations
In-Office
275K-315K Annually
Entry level
Artificial Intelligence • Natural Language Processing • Generative AI
The Role
Lead scientific enablement for Claude by designing and delivering workshops, hackathons, demos, notebooks, tutorials, and adoption programs. Build a scientist community, train internal Applied AI and Customer Success teams, create reusable playbooks, and represent scientists’ needs internally. The role requires hands-on AI-for-science expertise, LLM API prototyping, strong communication, program ownership, and scientific credibility across academic, biotech, pharma, or research environments.
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 Beneficial Deployments 

Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences — focusing on raising the floor for those who need it most.

About the Role

We're looking for an Applied AI Architect to join our Beneficial Deployments, Life Sciences team, focused on helping scientists everywhere get the most from Claude, especially Claude Science. You'll run enablements, workshops and hackathons, build demos that show what frontier models can do for the field, and grow a community of scientists building with Claude. You'll also scale scientific enablement inside Anthropic, so our Applied AI and customer teams can support scientists without you in the room.

Responsibilities
  • Be the DRI for scientific enablement: decide what to run, build the materials, deliver them, and measure whether research teams reach daily use of Claude.

  • Lead our programs for activating scientists at scale, such as LSVP and Claude for Researchers: set the goals, design the program and run it.

  • Build demos, notebooks and tutorials that show scientists what frontier models can do in their own work, and be an active voice where scientists share tools online (X, LinkedIn, etc.).

  • Scale scientific enablement inside Anthropic: train our Applied AI and Customer Success teams, and build playbooks they can run without you.

  • Build and lead a scientist community around Claude, and be its ambassador (and support ambassador programs), from small meetups to large conferences.

  • Be the voice of scientists inside Anthropic: turn what you hear into concrete asks and see them through to launch, and partner with Marketing and Comms so campaigns and content reach the scientific community.

You Might Be a Good Fit If You Have
  • Deep hands-on expertise with AI tools for science such as Claude Science: you know where they shine and where they break.

  • Real credibility as a scientist: hands-on experience doing science in academic labs, biotechs, pharma or research institutes, ideally as a user of the kind of tools you'll help scientists adopt. Experience building or running programs for scientific communities is a plus.

  • A track record of helping many scientific teams adopt a new tool through demos, trainings, workshops or hackathons.

  • Up to date on AI for science, such as agentic analysis and AI co-scientists, and able to explain it to working scientists.

  • Hands-on experience building with LLM APIs: you can prototype a working demo. You don't need to write production code.

  • Clear written and spoken communication: talks, tutorials and docs that scientists find useful.

  • A track record of taking programs or products from idea to results: you set the direction, did the work and were accountable for the outcome, often with no playbook.

  • Comfort operating in ambiguity: you bring clarity to fuzzy problems, wear multiple hats and do whatever it takes to further the mission.

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:
$275,000—$315,000 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 experience
  • Relevant field demonstrated through coursework, training, or professional experience
  • Deep hands-on expertise with AI tools for science, including Claude Science
  • Scientific credibility and hands-on experience conducting science in academic labs, biotechs, pharma, or research institutes
  • Track record helping scientific teams adopt new tools through demos, trainings, workshops, or hackathons
  • Current knowledge of AI for science, including agentic analysis and AI co-scientists
  • Hands-on experience building prototypes with LLM APIs
  • Clear written and spoken communication skills for talks, tutorials, and documentation
  • Track record taking programs or products from idea to measurable results
  • Ability to operate effectively in ambiguous environments and take on multiple responsibilities
  • Experience building or running programs for scientific communities

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.

  • Healthcare Strength — Health coverage for employees and dependents is described as comprehensive across medical, dental, and vision, alongside robust mental-health resources. Feedback suggests this breadth, paired with life and income protection, is a standout element of the package.
  • Parental & Family Support — Family-building support includes inclusive fertility benefits and an extended paid parental leave policy. Feedback suggests these programs are positioned as company‑wide and accessible rather than one‑off perks.
  • Wellbeing & Lifestyle Benefits — Everyday support spans wellness/time‑saver stipends, education and home‑office stipends, commuter benefits, daily meals/snacks, and relocation assistance. Feedback suggests these perks meaningfully supplement core pay and healthcare.

Anthropic Insights

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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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