Enterprise AI Solutions Engineer – Claude API Deployments

Anthropic; Seattle (WA); Hybrid; USD 200,000 - 320,000; Full time

Benefits offered by this job

Generous vacation

Parental leave

Flexible working hours

Office space

Job summary

Anthropic seeks a Technical Product Engineer to advise Digital Native Businesses on Claude API integration. You will guide customers from technical discovery to successful deployment, working with Sales, Product, and Engineering to tailor solutions and ensure safety and reliability.

You will help teams design architectures, develop evaluation frameworks, and share best practices for LLM usage and implementation patterns across customers.

Qualifications

• 4+ years in technical roles with customer focus.
• Production experience with LLMs, prompt engineering and deployment at scale.
• Strong Python or TypeScript skills and building production apps.
• Ability to navigate ambiguity and collaborate across teams.
• Excellent communication with diverse stakeholders.

Responsibilities

• Serve as a specialist technical advisor to Anthropic customers from discovery through deployment.
• Collaborate with account executives and solutions architects to map customer requirements to solutions.
• Influence architecture decisions by developing pilots, prototypes, and eval suites.
• Lead hands-on technical workshops and code reviews with customer teams.
• Identify common design patterns and share insights with Product and Engineering.
• Create scalable public/internal assets documenting LLM prompting, evaling, and architectures.
• Maintain knowledge of latest LLM developments and AI product stacks.
• Travel occasionally for workshops and implementation support.
• Engage in conferences, blogs, and white papers about AI topics.

Education

Bachelor's degree

Job description

Anthropic seeks a Technical Product Engineer to advise Digital Native Businesses on Claude API integration. You will guide customers from technical discovery to successful deployment, working with Sales, Product, and Engineering to tailor solutions and ensure safety and reliability.

You will help teams design architectures, develop evaluation frameworks, and share best practices for LLM usage and implementation patterns across customers.