Applied AI Architect, Industries

Anthropic Anthropic · AI Frontier · New York, NY +2 · Sales

This is a pre-sales architect role focused on helping large enterprises integrate and deploy Anthropic's Claude LLM. The role involves understanding customer requirements, architecting solutions, guiding customers through adoption, and creating technical content. It requires strong technical and customer-facing skills, with an emphasis on scaling LLM solutions for business challenges.

What you'd actually do

  1. Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation
  2. Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success
  3. Support customers building with both the Claude API and Claude for Work
  4. Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives
  5. Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack

Skills

Required

  • 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager
  • Experience working with enterprise customers, navigating complex buying cycles involving multiple stakeholders
  • Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more
  • 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
  • Comfortable with python
  • Familiarity with common LLM frameworks and tools or a background in machine learning or data science
  • Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities
  • A love of teaching, mentoring, and helping others succeed
  • Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities
  • 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

Nice to have

  • develop evals

What the JD emphasized

  • trusted technical advisor
  • architect innovative LLM solutions
  • address complex business challenges
  • safety and reliability
  • technical discovery
  • successful deployment
  • Claude's capabilities
  • develop evals
  • design scalable architectures
  • maximize the value of our AI systems
  • technical customer-facing roles
  • Solutions Architect
  • Sales Engineer
  • Technical Account Manager
  • enterprise customers
  • complex buying cycles
  • multiple stakeholders
  • build relationships
  • communicate technical concepts
  • diverse stakeholders
  • C-suite executives
  • engineering & IT teams
  • technical communication skills
  • translate customer requirements
  • technical and business stakeholders
  • scalable cloud architectures
  • integrating with enterprise systems
  • common LLM frameworks and tools
  • machine learning
  • data science
  • cross-organizational collaboration
  • working through trade-offs
  • balancing competing priorities
  • teaching
  • mentoring
  • helping others succeed
  • communication and interpersonal skills
  • complicated topics
  • easily understandable terms
  • external and internal stakeholders
  • thinking creatively
  • use technology
  • safe and beneficial
  • advancing safe AI systems