Description
Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
As a Demo Engineer, you'll build demos, reference implementations, and reusable tooling that help customer-facing teams make new capabilities tangible, relevant, and trustworthy. This role sits between product engineering, technical storytelling, and GTM execution. You'll own ambiguous, high-leverage problems end to end: prototyping an agentic experience for a new capability, then hardening it into something reliable that other teams can run on their own.
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 tie them to clear customer outcomes
- Turn recurring requests into reusable accelerators such as companion apps, templates, Skills, plugins, and self-service demo packages that scale across customer-facing teams
- Partner with GTM colleagues on high-impact customer moments, unblock critical technical gaps, and spot the patterns worth turning into 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 the bar for demo quality across accuracy, safety, reliability, usability, and adoption
- Decide when a customer need calls for a bespoke build and when it should become a shared capability
Requirements
- Proficiency in Python or TypeScript, with 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
- The ability to take an ambiguous capability or customer need to a working prototype quickly, and then make it reliable
- Clear communication of technical concepts to both technical and non-technical audiences, including sales and solutions teams
- Comfort collaborating across Product, Engineering, Marketing, Operations, and GTM teams
- Experience in a demo engineering, solutions engineering, sales engineering, forward deployed engineering, developer relations, or product engineering role
- A track record of building reusable internal tools, templates, or self-service assets that other teams adopted
- 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
- A history of turning field feedback into concrete product input that influenced a roadmap
- A passion for making powerful technology safe and beneficial, and a commitment to representing model capabilities accurately and honestly
The annual compensation range for this role is $240,000-$315,000 USD.