人工智能现场工程师，人工智能基础设施（远程 - 美国）
AI Field Engineer, AI Infrastructure (Remote - US)
Lavendo 与初创企业和高增长公司合作，帮助他们招聘顶级销售、GTM 和技术人才。此职位属于我们的一个客户；在我们了解你并确认双方匹配度后，我们会分享关于公司和面试流程的详细信息。
关于公司
我们的客户是一家快速扩展的 AI 基础设施公司，帮助企业和 AI 原生初创公司构建、微调和部署自己的专用 AI 模型——不再依赖他人的黑盒 API。他们的平台已在一些科技领域最知名的企业中投入生产，涵盖文本、图像、嵌入、音频和多模态工作负载。最近以 175 亿美元估值完成 D 轮融资，这是一家真正具备规模、真实客户和强大势头的公司。
使命
他们相信下一代伟大的产品将由那些拥有自己 AI 堆栈的公司打造，而不仅仅是租用它。他们的使命是为在前沿构建产品的团队，真正实现开放模型 AI 基础设施的高速、灵活和生产级性能。
机会
这是一个前移部署的工程角色，你永远不会远离终端或有 VP 在上面的白板。你将直接与 VP 工程师、AI/ML 首席和财富 500 强企业及前沿 AI 原生初创公司的 CTO 级合作伙伴合作，从第一次发现通话一直到生产环境，全程负责技术胜利。目前有两个方向开放——企业端和 AI 原生端——相同角色，不同客户群体，我们会讨论哪个更适合你的背景和兴趣。
你会做什么
- 独立完成完整的售前现场流程：发现、POC 规划、模型评估和最终模型选择
- 在客户环境中交付实际的生产代码——这是实际的构建工作，而不是咨询幻灯片
- 使用 vLLM、SGLang 和 TensorRT-LLM 等框架部署和微调开源模型 LLM（SFT 基线，DPO/RFT 是加分项）
- 作为真正的合作伙伴与你的销售同事协作，塑造交易策略，而不仅仅是支持它
- 在客户的组织内部建立关系，从工程师到高管，并知道如何在两个层面推动交易前进
你带来的能力
- 3 年以上面向客户的 AI/ML 角色经验——解决方案架构师、前移部署工程师、客户成功工程师、应用 AI 工程师、销售工程师，或具有真实客户接触的 AI/ML 方向软件工程师
- 在开源模型 LLM 推理和/或微调方面有实际动手经验
- 有超大规模云服务商经验
查看英文原文
Lavendo partners with startups and high‑growth companies to help them hire top‑tier sales, GTM, and technical talent. This role is with one of our clients; we’ll share full details about the company and interview process as we get to know you and confirm mutual fit.
About the Company
Our client is a fast-scaling AI infrastructure company that helps enterprises and AI-native startups build, fine-tune, and serve their own specialized AI models — no more relying on someone else's black-box API. Their platform runs in production for some of the most recognizable names in tech, spanning text, image, embedding, audio, and multimodal workloads. Freshly backed by a Series D at a $17.5B valuation, this is a company with real scale, real customers, and real momentum behind it.
The Mission
They believe the next generation of great products will be built by companies that own their AI stack, not just rent it. Their mission is making open-model AI infrastructure genuinely fast, flexible, and production-grade for the teams building at the frontier.
The Opportunity
This is a forward-deployed engineering role where you're never far from either a terminal or a whiteboard with a VP on it. You'll work directly with VP Engineering, Head of AI/ML, and CTO-level partners at Fortune 500 enterprises and cutting-edge AI-native startups, owning the technical win from the first discovery call all the way through production. Two tracks are open — Enterprise and AI-Native — same role, different customer base, and we'll talk through which fits your background and interests best.
What You'll Do
- Run the full pre-sales field cycle yourself: discovery, POC scoping, model evals, and final model selection
- Ship real production code inside customer environments — this is hands-on building, not advisory slides
- Deploy and fine-tune open-model LLMs using frameworks like vLLM, SGLang, and TensorRT-LLM (SFT baseline, DPO/RFT a big plus)
- Act as a true partner to your sales counterpart, shaping deal strategy rather than just supporting it
- Build relationships across a customer's org, from engineers to executives, and know how to move a deal forward on both levels
What You Bring
- 3+ years in a client-facing AI/ML role — Solutions Architect, Forward-Deployed Engineer, Customer Success Engineer, Applied AI Engineer, Sales Engineer, or an AI/ML-focused SWE with genuine customer exposure
- Real hands-on experience with open-model LLM inference and/or fine-tuning
- Hyperscaler experience in an AI context (AWS, Azure, or GCP)
- Strong Python skills, comfort with GPU infrastructure and Kubernetes
- A background at an AI-native company or a SaaS company genuinely building AI features (not bolting them on)
- Full-time work history, and openness to travel to enterprise customers as needed
Key Success Drivers
You're the rare person equally comfortable debugging inference trade-offs with an ML engineer in the morning and presenting the same trade-offs to a VP by afternoon. You bring genuine customer obsession alongside technical depth — this role rewards people who've shipped things themselves, not just advised on them. Strong candidates own outcomes end-to-end and know how to build trust across both engineering and executive stakeholders.
Why Join?
Compensation & Equity
- Base salary $176K–$224K, OTE $220K–$280K
- Performance-based variable compensation, paid quarterly
- Meaningful equity in a fast-growing, well-funded startup — Series D at a $17.5B valuation
Location
· Remote-friendly with hubs in New York and San Mateo — flexibility to work from anywhere in the US with regular travel to enterprise customers
Visa Sponsorship Details
- Open to visa transfers (e.g. OPT, H1B transfers)
- Open to visa sponsorships (e.g. new H1B, TN)
Benefits
· Comprehensive benefits package
Interviewing Process
- Recruiter/hiring manager screen (30 min): logistics, motivation, fit
- Take-home (5 days): build a working text-to-SQL system
- Culture + live coding (45 min): product discussion, extend your code live
- Discovery + hiring manager (45 min): live discovery role-play
- Executive conversation (30 min): short demo + values discussion
We are proud to be an equal opportunity workplace and consider all qualified applicants without regard to race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran or military status, gender identity or expression, sexual orientation, or any other characteristic protected by law.
Compensation Range: $220K - $280K
Originally posted on Himalayas