Applied AI, Research Engineer en Anthropic

Híbrido - San Francisco, CA; New York City, NY

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The Applied AI Research Engineer role at Anthropic focuses on bridging model capabilities with customer needs. The engineer will work with product, sales, and research teams to evaluate new models, build demos, prototype solutions, and create enablement materials. They will engage with strategic customers, synthesize insights, and support high-value accounts while occasionally traveling for workshops. The role requires deep technical expertise, strong communication, and a passion for safe, beneficial AI.

Salary

USD 300,000 - 400,000

Requirements

Skills

  • 6+ years of experience as a Software Engineer, Technical Product Manager, Forward Deployed Engineer, AI startup founder, or similar technical role
  • Track record of going deep on technical problems and translating learnings into materials, training, or tools
  • Strong technical aptitude with proficiency in at least one programming language
  • Meaningful experience building with large language models, including shipping LLM-powered products, developing agents or workflows, or integrating models into production systems
  • Experience designing evaluations, building prototypes, or developing technical enablement for complex products
  • Ability to quickly build domain expertise in new product areas and become a credible technical voice on new topics
  • Curiosity about what AI models can actually do and ability to probe new capabilities
  • Excellent communication and interpersonal skills, able to convey complicated topics to diverse stakeholders, including exec-level
  • Ability to navigate and execute amidst ambiguity, and to flex into different domains based on business problem
  • Collaborative, service-oriented mindset – go-to-market at Anthropic is a team sport
  • Passion for thinking creatively about how to use technology safely and beneficially

Responsibilities

  • Embed with product teams to build deep technical expertise on new products and capabilities as they develop, becoming the field's go-to expert in your domain
  • Own the technical<> GTM handshake for model and product launches – early testing, field readiness assessments, and ongoing capability education throughout the model lifecycle
  • Build demos, evals, and prototypes that showcase customer-relevant model and product capabilities, and define what good performance looks like in important domains
  • Develop enablement materials like playbooks, training sessions, and reference architectures in partnership with Technical Enablement, so Applied AI teams can effectively position and deliver new capabilities from day one
  • Engage hands‑on with strategic customers facing novel technical challenges in your domain, discover solutions, then package learnings into scalable approaches for the broader field
  • Synthesize insights from across customer engagements and work with Product and Research to land them. Identify adoption patterns, common blockers, and capability gaps that should inform our research and product roadmaps
  • Partner with Sales and Applied AI teams to support high-value accounts that need specialized domain knowledge
  • Travel occasionally to customer sites for workshops, implementation support, and research collaboration

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