The opportunity
Crusoe is on a mission to accelerate the abundance of energy and intelligence . As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads.
What you'll do
Agentic Reference Systems: Architect and ship end-to-end reference agents and starter kits on Crusoe that developers can use as a starting point for production, covering tool use, MCP, multi-agent orchestration, RAG, structured outputs, memory, and evals.
Examples & Documentation: Own the code examples, tutorials, and documentation that help developers go from first API call to working agent, and keep them tested and up to date as the ecosystem changes.
Open Source & GitHub: Own Crusoe's developer-facing GitHub presence, including examples, cookbooks, and integrations. Contribute upstream to agent frameworks, inference engines, and developer tooling (for example LangGraph, LlamaIndex, CrewAI, Pydantic AI, the OpenAI Agents SDK, MCP, vLLM, and SGLang) so they work well with Crusoe.
Technical Content & Video: Turn the systems you build into content developers rely on: deep-dive blog posts, notebooks, YouTube videos, livestreams, and short technical clips.
Building in Public: Share your work on X, LinkedIn, YouTube, Discord, Reddit, Hacker News, etc. Answer technical questions, review community projects, and become a trusted technical voice in the agent and open-source community.
Use-Case Blueprints: Partner with GTM/Solutions Engineering to spot recurring customer patterns and turn them into open reference architectures for developer segments such as Physical AI, robotics, simulation, and other industry verticals.
What they're looking for
- Product & Research Partnership: Join Product, Engineering, and Research workflows. Test features and models before launch, make sure samples and docs are ready on launch day, and bring developer friction back as concrete product input, following each issue until it is fixed or explicitly deprioritized.
- Talks & Workshops: Give technical talks, live demos, and hands-on labs at conferences, meetups, hackathons, and workshops.
- Engineering Experience: 5+ years as a software engineer, ML engineer, applied AI engineer, forward-deployed engineer, or in a similar hands-on engineering role, with strong Python. A Developer Relations title is not required.
- Engineering Credibility: Ability to earn credibility with both AI infrastructure engineers and ML/AI engineers.
