Job description

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: As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping customers understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your technical depth with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability. As a Commercial Solutions Architect, you'll go deep with priority accounts as a hands-on builder, while creating reusable blueprints, demos, and enablement that extend Claude's reach across the broader Commercial book of business. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation Serve as the primary technical advisor to customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams and stakeholders to drive customer success Support customers building with the Claude API, Claude Code, and Claude for Enterprise Ship working code. Build prototypes and proof-of-concepts hands-on, develop eval frameworks, and write near-production examples that customers can extend Build reusable blueprints, demos, and enablement assets that scale across customers Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases Identify common integration patterns and contribute insights back to our Product and Engineering teams Travel occasionally to customer sites for workshops, technical deep dives, and relationship building Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: 3+ years of highly technical experience as a software engineer (or equivalent) with some customer-facing exposure, OR 3+ years as a Solutions Architect, Sales Engineer, or Technical Account Manager with strong hands-on building experience A builder identity. You've shipped real software, you have technical taste, and you care about the craft of what you build A systems mindset. When you see a problem, your instinct is to ask "how do I make this reusable." You'd rather build one thing that serves ten customers than ten things that serve one each Strong coding ability. You ship prototypes regularly and can work in a real codebase, not just notebooks. Comfort with Python expected Strong ability to build trust with technical stakeholders and adjust your communication for varied audiences Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Familiarity with common LLM frameworks and tools, or a background in machine learning or data science Comfort operating in early-stage, ambiguous environments where the playbook doesn't exist yet, and a track record of building structure as you go Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems 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: $240,000 — $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.

Requirements

Must-haves

Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation
Support customers building with the Claude API, Claude Code, and Claude for Enterprise
Ship working code. Build prototypes and proof-of-concepts hands-on, develop eval frameworks, and write near-production examples that customers can extend
Build reusable blueprints, demos, and enablement assets that scale across customers
Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack
Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases
Identify common integration patterns and contribute insights back to our Product and Engineering teams
Travel occasionally to customer sites for workshops, technical deep dives, and relationship building
Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns
You may be a good fit if you have:
A builder identity. You've shipped real software, you have technical taste, and you care about the craft of what you build
A systems mindset. When you see a problem, your instinct is to ask "how do I make this reusable." You'd rather build one thing that serves ten customers than ten things that serve one each
Strong coding ability. You ship prototypes regularly and can work in a real codebase, not just notebooks. Comfort with Python expected
Strong ability to build trust with technical stakeholders and adjust your communication for varied audiences
Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders
Experience designing scalable cloud architectures and integrating with enterprise systems
Familiarity with common LLM frameworks and tools, or a background in machine learning or data science
Comfort operating in early-stage, ambiguous environments where the playbook doesn't exist yet, and a track record of building structure as you go
Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities
A love of teaching, mentoring, and helping others succeed
Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems
The annual compensation range for this role is listed below.
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

Nice-to-haves

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Application prep

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Keywords to mirror

aillmgoapipythonmachine learning

Platform: greenhouse
Effort: quick

Benefits

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Vision

Parental Leave