Solutions Architect, Applied AI (Startups)
San Francisco, CA | New York City, NYFull-TimeLeadAI / Data Science
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 a Solutions Architect on the Startups Applied AI team at Anthropic, you will win the trust of founders and engineers by being an exceptional technical partner, helping startups successfully build on the Claude Developer Platform as they grow from early product to scale. You'll combine deep technical expertise with a builder-first mindset to help startups architect innovative LLM solutions, win technical evaluations, and get the most out of Claude.
- Working closely with Account Executives and the broader Sales, Product, and Engineering teams, you'll guide startups from initial technical discovery through successful deployment and beyond. You'll leverage your expertise to help founders understand Claude's capabilities, develop evals, and design architectures that maximize the value of our AI systems.
Responsibilities
- Partner with Account Executives to deeply understand startup requirements, translate them into technical solutions, and serve as a trusted technical advisor throughout the Claude adoption journey from initial evaluation through deployment and expansion
- Win technical evaluations that demonstrate why Claude is the best foundation for what startups are building, helping them develop evaluation frameworks to measure Claude's performance for their specific use cases
- Build technical credibility with founders, founding engineers, and startup engineering teams by speaking their language, understanding their build patterns, and guiding technical architecture decisions
- Gather insights on how startups are building with Claude, identify emerging use cases and deployment patterns, and deliver feedback to Product and Engineering teams
- Travel to customer sites, startup-focused events, and industry conferences for workshops, technical deep dives, and relationship building
You may be a good fit if you have
- 3+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, Forward Deployed Engineer, or technical founder who has done founder-led sales
- Experience working with startups or high-growth technology companies; you understand the velocity and constraints of early-stage companies
- Strong builder credibility through experience as a software engineer or technical founder; you speak the language of builders and have the presence to earn the trust of technical founders and startup engineering teams
- Deep technical proficiency with building and scaling AI products, a pulse on AI engineering best practices, and the ability to demonstrate why Claude is the best foundation
- Hands-on experience building and deploying LLM-powered applications in production, with expertise in context engineering, evaluation frameworks, and modern AI architectures
- Strong technical communication skills with the ability to translate complex AI concepts into actionable insights for founders and engineering teams
- Track record of selling technical products in competitive markets
- Comfortable with Python and familiarity with common LLM frameworks, tools, and integration patterns
- Passion for making powerful technology safe and societally beneficial
- 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.
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.
