Applied AI Engineer, Enterprise Tech na Anthropic

Híbrido - San Francisco, CA, New York City, NY, Seattle, WA

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You will serve as a technical product engineer on Anthropic’s Applied AI team, advising Digital Native Businesses on integrating Claude API into their products. You’ll collaborate with internal Sales, Product, and Engineering teams to guide customers from technical discovery to deployment, develop evaluation frameworks, conduct workshops, and document best practices, while maintaining high safety and reliability standards.

Salary

USD 200,000 - 320,000

Requirements

Skills

  • 4+ years of experience in technical roles such as Forward Deployed Engineer, Software Engineer or Technical Product Manager with a desire to work closely with customers. Former technical founders are also encouraged to apply.
  • Production experience with LLMs including advanced prompt engineering, agent development and frameworks, evaluation frameworks, transcript analysis, MCP, and deployment at scale
  • Strong programming skills with proficiency in Python or TypeScript and experience building production applications
  • Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems
  • High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity
  • Passion for advancing safe, beneficial AI systems through creative technical applications
  • Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach
  • Bachelor’s degree or equivalent combination of education, training, and/or experience

Responsibilities

  • Serve as a specialist technical advisor to Anthropic customers as they deploy new products & workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success
  • Partner with account executives and solutions architects to translate customer business requirements into technical solutions
  • Influence technical architecture decisions and customer product strategy by developing customized pilots, prototypes, and evaluation suites
  • Lead hands-on technical workshops and code reviews with customer engineering teams
  • Identify common design patterns and contribute insights back to our Product and Engineering teams
  • Create scalable public and internal assets, documenting the latest LLM prompting, evaling, agentic, and architecture techniques
  • Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks
  • Travel occasionally to customer sites for workshops, implementation support, and building relationships
  • Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space

Technologies

PythonTypeScriptLLMClaude APIprompt engineeringagent developmentevaluation frameworksMCP

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