Staff AI Engineer, Developer Relations Engineering

Sunnyvale, CA - US, onsite, senior, full time, USD 1,80,000–2,20,000 / year, 5+ years

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SFT
vLLM
Azure
CrewAI
SGLang
OpenAI Agents SDK
LangGraph
Pydantic AI
GCP
LoRA
RAG
RL
MCP
AWS
LlamaIndex
Python

About the role

Crusoe is hiring an AI Engineer for our Developer Relations Engineering team: an engineer who builds agentic AI systems and enjoys showing other developers how they work. You will build reference agents, open-source integrations, and sample applications on Crusoe Cloud and Crusoe Managed Inference.

In this role, you will lead technical content creation, community engagement, and developer outreach across AI infrastructure and managed services workloads. You will produce documentation, tutorials, white papers, sample applications, and video guides.

You will partner with the Product, Engineering, Research, and GTM/Solutions Engineering teams and work across the open-source agent ecosystem.

You will spend most of your time building and then sharing what you build.

What You'll Be Working On:

* 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.

* 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.

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What they are looking for

Senior Level

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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. When you join Crusoe, you join a team that is building the future, faster.

We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.

We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.

If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.

* 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.

* Agentic AI: Hands-on experience building LLM applications and agents with tool calling, MCP, retrieval, memory, and evaluation, using one or more frameworks such as LangGraph, LlamaIndex, CrewAI, Pydantic AI, or the OpenAI Agents SDK. You have well-formed opinions about what works and what breaks in production.

* Cloud Infrastructure: Experience working with cloud computing platforms (such as AWS, GCP, or Azure) or managed AI solutions, with a foundational understanding of cloud infrastructure concepts.

* Inference & Model Serving: Working knowledge of how models are served, including OpenAI-compatible APIs, open-weight models, and serving engines such as vLLM or SGLang. You can explain cost and latency tradeoffs credibly.

* Public Track Record: Evidence of sharing technical work in public through GitHub repos, open-source contributions, blog posts, videos, talks, or an active technical presence on social platforms. Please include links when you apply.

* Technical Communication: Strong communication skills across written and verbal formats, including technical documentation, white papers, video explainers, and presentation decks.

* Ownership & Collaboration: You work well across teams, set your own priorities, and ship in a fast-moving environment.

* Travel Requirement: Ability to travel up to 20%.

* Education: Bachelor's/Master's/PhD degree in Computer Science, or equivalent practical experience.

* Maintainer or significant contributor to an open-source AI, agent, or inference project

* Experience producing technical video content such as YouTube tutorials, livestreams, or screencasts

* Experience fine-tuning or post-training open-weight models (SFT/RL/LoRA)

* An existing technical audience that trusts your views on models, agents, and tooling

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