Applied AI Demo Engineer

Anthropic•San Francisco, CA

4d•$240,000 - $315,000•Hybrid

About The Position

Anthropic is hiring an Applied AI Demo Engineer to build demos, reference implementations, and reusable tooling that help customer-facing teams demonstrate Claude’s capabilities quickly, clearly, and credibly. The role combines product engineering, technical storytelling, and go-to-market execution. The engineer will take ambiguous, high-impact problems from prototype through to reliable solutions that other teams can use independently, working with Product, Engineering, Marketing, Operations, sales, and solutions teams. Insights from customer-facing work will inform product feedback, launch readiness, and broader improvements. Demonstrations should represent model capabilities accurately and honestly, with attention to safety, reliability, usability, and adoption. Anthropic expects staff to work from one of its offices at least 25% of the time under its current hybrid policy, though some roles may require more office time. The minimum education is a bachelor’s degree or an equivalent combination of education, training, and/or experience; the required field of study must be relevant to the role as demonstrated through coursework, training, or professional experience. Required years of experience correlate with the position’s internal job level. Visa sponsorship may be available, but is not guaranteed for every role or candidate.

Requirements

Proficiency in Python or TypeScript and experience shipping working software end to end.
Hands-on experience building applications or agents on top of LLM APIs, including prompting, tool use, and retrieval.
Experience designing integrations with third-party APIs, data sources, and services.
Ability to take an ambiguous capability or customer need to a working prototype quickly and then make it reliable.
Ability to communicate technical concepts clearly to technical and non-technical audiences, including sales and solutions teams.
Comfort collaborating across Product, Engineering, Marketing, Operations, and go-to-market teams.
Minimum education of a bachelor’s degree or equivalent combination of education, training, and/or experience.
A field of study relevant to the role, demonstrated through coursework, training, or professional experience.
Required years of experience correlate with the internal job level requirements for the position.
Commitment to representing model capabilities accurately and honestly.

Nice To Haves

Experience in demo engineering, solutions engineering, sales engineering, forward deployed engineering, developer relations, or product engineering.
Track record of building reusable internal tools, templates, or self-service assets adopted by other teams.
Hands-on experience with Claude Code, the Claude Agent SDK, the Model Context Protocol (MCP), Skills, or plugins.
Experience building evaluation or validation harnesses for AI systems, including reliability checks and graceful fallbacks.
Experience building always-on or scheduled agentic systems that automate internal workflows.
Experience building synthetic or sanitized datasets that make demos realistic without exposing sensitive information.
Front-end or product design skills that help demos feel polished and intuitive.
Experience supporting product launches or running launch-readiness programs.
History of turning field feedback into concrete product input that influenced a roadmap.
Passion for making powerful technology safe and beneficial.

Responsibilities

Own demo readiness for new and priority Claude capabilities, including environments, integrations, synthetic data, evaluations, reliability checks, and fallback paths.
Build prototypes, agents, and reference flows that make complex capabilities concrete and connect them to clear customer outcomes.
Turn recurring requests into reusable accelerators, including companion apps, templates, Skills, plugins, and self-service demo packages.
Partner with go-to-market colleagues on high-impact customer moments, unblock technical gaps, and identify patterns that should become shared assets.
Build internal agentic systems that automate demo preparation, validation, and asset maintenance so demos stay current as products change.
Translate patterns from customer-facing work into product feedback, launch-readiness priorities, and systemic improvements with Product and Engineering.
Define and raise standards for demo accuracy, safety, reliability, usability, and adoption.
Determine when a customer need calls for a bespoke build and when it should become a shared capability.