创始部署工程师
Founding Forward Deployed Engineer
我们是一家隐秘型控股公司，专注于收购和运营被忽视但至关重要的行业中的软件业务——这些是支撑实体经济的系统，但被硅谷所忽略。我们正在从内到外重建它们，使其成为原生AI系统。
我们规模小、资金充足、行动迅速。这不是一个研究实验室。这是一个有真实客户、真实收入和真实损益表的开发团队。
职位描述
你将成为AI工程师。你将负责：
- 构建行业特定的GPT：编码每个垂直领域专业知识的推理层。
- 将原生AI功能直接嵌入我们的原生记录系统中：不是附加的聊天机器人。核心工作流程的替代方案。能够完成工作的代理。
- 将遗留的记录系统数据集迁移到新的原生AI系统中：核心工作流程的替代方案。能够完成工作的代理。
- 使其可重复：我们引入组合中的每一家新公司都应从你建立的指南、模型堆栈、评估工具和基础设施中受益。
- 管理我们运营公司的AI人才：你将在每个子公司的AI工程师中扮演球员兼教练的角色。
分工：90%用于开发。10%用于管理。如果这个比例让你感到不安，那么这个职位不适合你。如果你对此感到兴奋，请继续阅读。
你会做什么…
- 在入职的前30天内，将一个可用的领域特定代理部署到实际客户环境中
- 构建评估基础设施，使我们能够衡量这些代理是否真正替代了人工流程（而不是感觉）
- 根据每个垂直领域的经济情况，对前沿模型和开源模型进行微调、蒸馏或路由
- 与客户一起工作。观察他们的工作方式。对其流程进行监控。重新构建它们
- 编写AI工程指南，让未来每个组合公司都能在第一天继承它
你是谁…
- 你首先是一个建造者。你已经交付了人们实际使用的项目。无论是独自一人还是作为明确的技术负责人。
- 你是一个前线工程师。你会飞往客户现场，坐在他们的办公室里，在写任何代码之前先理解业务。
- 你曾被称为10倍工程师，而这并不是在自我评价中。
- 你对何时使用微调、提示、RAG、代理或工具链有强烈的观点，并且能用数据来支持这些观点。
- 你在生产环境中使用过当前的前沿技术栈（Claude、GPT、Gemini、开源模型），而不仅仅是在Jupyter笔记本中。
- 你对幻灯片演示过敏，能适应模糊性、小型团队和不那么光鲜的行业。
查看英文原文
We're a stealth holding company acquiring and operating software businesses in overlooked, mission-critical industries - the systems that run the physical economy but have been ignored by Silicon Valley. We're rebuilding them as AI-native from the inside out.
We're small, well-capitalized, and moving fast. This is not a research lab. This is a build shop with real customers, real revenue, and real P&Ls.
The Role
You will be the AI engineer. You'll own:
- Building the industry-specific GPT: the reasoning layer that encodes the domain expertise of each vertical we operate in.
- Embedding AI-native functionality directly into our AI-native system of record: not bolt-on chatbots. Core workflow replacement. Agents that do the job.
- Moving legacy systems of record datasets into new ai-native ones: Core workflow replacement. Agents that do the job.
- Making it repeatable: Every new company we bring into the portfolio should benefit from the playbook, model stack, eval harness, and infra you build.
- Managing AI talent across our operating companies: you'll be a player-coach for the AI engineers embedded at each sub.
Split: 90% building. 10% managing. If that ratio scares you, this isn't your role. If it excites you, keep reading.
What You'll Do…
- Ship a working domain-specific agent into a live customer environment in your first 30 days
- Build the eval infrastructure that lets us measure whether these agents are actually replacing human workflows (not vibes)
- Fine-tune, distill, or route across frontier + open models depending on the economics of each vertical
- Sit with customers. Watch them work. Instrument their workflows. Rebuild them.
- Write the AI engineering playbook that every future portfolio company inherits on day one
Who You Are…
- You are a builder first. You've shipped things people actually use. Alone or as the clear technical lead.
- You are a forward-deployed engineer. You'll fly to a customer site, sit in their office, and understand the business before you write a line of code.
- You've been called a 10x engineer and it wasn't in a self-review.
- You have strong opinions about when to fine-tune vs. prompt vs. RAG vs. agent vs harness and you can defend them with numbers.
- You've built with the current frontier stack (Claude, GPT, Gemini, open models) in production, not just in a Jupyter notebook.
- You are allergic to slide decks and comfortable with ambiguity, small teams, and unglamorous industries.
What This Role Is Not…
- A research role. We ship.
- A management role. You build.
- A "Head of AI" title for LinkedIn. You will be in the codebase daily.
- A place for people who need process, roadmaps handed to them, or a 20-person team to feel productive.
We are focused on building a diverse and inclusive workforce. If you’re excited about this role, but do not meet 100% of the qualifications listed above, we encourage you to apply.
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Atomic is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law.
Please review our CCPA policies here.