Staff AI Engineer, Developer Relations Engineering

Crusoe is hiring a Staff AI Engineer for Developer Relations Engineering to build agentic AI systems and make them easy for developers to adopt. This role focuses on shipping reference agents, open-source integrations, and sample applications on Crusoe Cloud and Crusoe Managed Inference, then turning that work into the tutorials, code examples, and community engagement developers rely on.

You will lead technical content creation and developer outreach while collaborating across Product, Engineering, Research, and GTM/Solutions Engineering. If you like moving from hands-on implementation to clear guidance, this is a strong fit.

What you will do

• Architect and ship end-to-end reference agents and starter kits on Crusoe that developers can use as a starting point for production, including tool use, MCP, multi-agent orchestration, RAG, structured outputs, memory, and evals.
• Own code examples, tutorials, and documentation that take developers from their first API call to a working agent, keeping materials tested and current as the ecosystem evolves.
• 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.
• Translate what you build into developer-facing content such as deep-dive blog posts, notebooks, YouTube videos, livestreams, and short technical clips.
• Share your work on X, LinkedIn, YouTube, Discord, Reddit, and Hacker News; answer technical questions, review community projects, and act as a trusted technical voice.
• Partner with GTM/Solutions Engineering to spot recurring customer patterns and convert them into open reference architectures for segments such as Physical AI, robotics, simulation, and other verticals.
• Work within Product/Engineering/Research workflows by testing features and models before launch, ensuring samples and documentation are ready on launch day, and feeding developer friction back as concrete product input.
• Give technical talks, live demos, and hands-on labs at conferences, meetups, hackathons, and workshops.

What you bring

• 5+ years as a software engineer, ML engineer, applied AI engineer, forward-deployed engineer, or similar hands-on role, with strong Python.
• Ability to earn credibility with both AI infrastructure engineers and ML/AI engineers.
• 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.
• Strong, production-informed views on what works and what breaks.
• Working knowledge of cloud computing platforms (such as AWS, GCP, or Azure) or managed AI solutions, with foundational understanding of cloud infrastructure concepts.
• Knowledge of model serving, including OpenAI-compatible APIs, open-weight models, and serving engines such as vLLM or SGLang.
• Ability to explain cost and latency tradeoffs credibly.
• Proven public sharing through GitHub, open-source, blog posts, videos, talks, or an active technical presence on social platforms (include links when applying).
• Strong communication across written and verbal formats, including technical documentation and presentation materials.
• Ability to work cross-team, set priorities, and ship in a fast-moving environment; travel up to 20%.
• Bachelor’s/Master’s/PhD in Computer Science, or equivalent practical experience.

Technologies you’ll work with

Python, LangGraph, LlamaIndex, CrewAI, Pydantic AI, OpenAI Agents SDK, MCP, vLLM, SGLang, AWS, GCP, Azure, OpenAI-compatible APIs

Compensation & benefits

• Salary range: USD 180,000 - 220,000 per year plus bonus.
• Restricted Stock Units included in all offers.
• Paid time off, paid holidays, and leave of absence programs.
• Comprehensive health, dental & vision insurance.
• Employer contributions to an HSA account.
• Paid parental leave.
• Paid life insurance, short-term and long-term disability.
• Professional development & tuition reimbursement.
• Mental health & wellness support.
• Commuter benefits (parking & transit) and a cell phone stipend.
• 401(k) Retirement plan with company match up to 4% of salary.
• Volunteer time off.
• Global travel insurance & emergency assistance.
• Daily meals allowance.
• Additional perks & programs specific to location.

Bonus points

• 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.