Anthropic
Applied AI Architect, Enterprise Tech
$240K–$380K
San Francisco, CA +3 · Full-time · Posted Aug 7, 2026
- Location
- San Francisco, CA
New York City, NY
Seattle, WA
San Francisco, California, United States - Experience
- 5+ years in technical customer-facing roles; the logistics section states years required correlate with internal job-level requirements.
- Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience; field relevant to the role, demonstrated through coursework, training, or professional experience.
- Visa sponsorship
- Visa sponsorship is available, but not for every role or candidate; if an offer is made, Anthropic will make every reasonable effort to obtain a visa and provides an immigration lawyer.
About the job
Serves as a pre-sales technical advisor to enterprise customers, designing and guiding adoption of Claude solutions from discovery and evaluation through deployment.
What you'll do
- Translate customer requirements into technical solutions and advise on Claude adoption, architecture, and integration.
- Help customers build with the Claude API and Claude for Work, and develop evaluation frameworks for their use cases.
- Create technical content, coordinate across internal teams, and share integration insights with Product and Engineering.
What they ask for
- 5+ years of experience in technical customer-facing roles, such as Solutions Architect, Sales Engineer, or Technical Account Manager.
- Experience working with enterprise customers and complex, multi-stakeholder buying cycles.
- Experience designing scalable cloud architectures and integrating with enterprise systems.
- Comfortable with python.
Nice to have
- Familiarity with common LLM frameworks and tools, or a background in machine learning or data science.
Pay
$240,000 — $380,000 USD (OTE; includes target sales commissions/bonuses and annual base salary)
Tools
Claude, Claude API, Claude for Work, python
AI focus
Help enterprise customers evaluate and deploy Claude solutions, including developing use-case-specific evaluations and scalable integrations, while maintaining safety and reliability.
Model-written summary · the original posting is authoritative