高级全栈人工智能工程师 – DeepLaw
Senior Full-Stack AI Engineer – DeepLaw
DeepLaw 正在构建一个智能 AI 代理，用于审查合同——不仅关注法律风险，还从商业角度出发。我们的目标是帮助创始人、运营人员和法务团队理解合同对他们实际意味着什么：合同依赖的假设、它所反映的权衡，以及它如何与他们的价值观和目标一致（或冲突）。
我们正在寻找一名高级工程师，从零开始领导技术开发。你将构建代理系统，连接各个部分（UI ↔ LLM ↔ 数据层），并与创始产品经理密切合作，定义产品和路线图。
🛠 你将构建
- 核心 AI 代理流程——可能涉及提示编排、检索（RAG）和微调
- 与代理交互的用户体验和工具（基础网页 UI、标注、结构化合同数据）
- 支持迭代和实验的数据 + 模型基础设施
- MVP 功能：假设映射、合同诊断、价值对齐反馈等
- 用于工作原型的部署设置（CI/CD、云基础设施、最小运维）
- 帮助定义“价值对齐”合同审查在产品和代码中的实际含义
🧩 你是什么样的人
- 5 年以上全栈工程师或 AI 工程师经验，最好是在初创公司
- 有在生产环境中使用 LLM 的经验：提示工程、LangChain、AutoGen 或类似工具
- 熟悉基于代理的架构和 RAG 流程
- 能够搭建网页应用、API、向量存储和微调循环
- 附加优势：有法律科技经验、处理过合同，或对推理导向的 AI 感兴趣
- 具备协作精神，能够自主工作，并热衷于从零到一的产品挑战
🧠 这个职位的独特之处
- 参与 LLM 在现实世界中的应用，超越摘要功能
- 从第一天起就直接与一位注重产品的创始人合作
- 高度自主，决策迅速，从零开始的架构设计
- 不仅影响我们构建什么——还影响我们如何工作以及下一步招聘谁
🔧 你可能会接触到
- OpenAI、Claude、开源模型
- LangChain / AutoGen / 或自建的代理层
- Pinecone、Weaviate、Postgres、Supabase
- React/Next.js 或类似的 UI 框架
- GCP、AWS、Vercel 或轻量级基础设施以实现快速迭代
Originally posted on Himalayas
查看英文原文
DeepLaw is building an intelligent AI agent that reviews contracts — not just for legal risk, but through a business lens. Our goal is to help founders, operators, and legal teams understand what a contract actually means for them: the assumptions it relies on, what trade-offs it reflects, and how it aligns (or conflicts) with their values and goals.
We're looking for a Senior Engineer to lead technical development from scratch. You’ll build the agent system, connect the pieces (UI ↔ LLM ↔ data layer), and work closely with the founding PM to define the product and roadmap.
🛠 What You’ll Build
- The core AI agent pipeline — likely involving prompt orchestration, retrieval (RAG), and fine-tuning
- UX and tooling for interacting with the agent (basic web UI, annotation, structured contract data)
- Data + model infrastructure to support iteration and experimentation
- MVP features: assumption mapping, contract diagnostics, value-aligned feedback, etc.
- Deployment setup for a working prototype (CI/CD, cloud infra, minimal ops)
- Help define what “value-aligned” contract review actually means in product and code
🧩 Who You Are
- 5+ years of experience as a full-stack engineer or AI engineer, ideally at startups
- Experience with LLMs in production: prompt engineering, LangChain, AutoGen, or similar
- Familiar with agent-based architectures and RAG pipelines
- Comfortable spinning up web apps, APIs, vector stores, and fine-tuning loops
- Bonus: experience with legal tech, working with contracts, or interest in reasoning-focused AI
- Collaborative, autonomous, and energized by zero-to-one product challenges
🧠 Why This Role Is Unique
- Work on a real-world application of LLMs that goes beyond summarization
- Partner directly with a product-minded founder from day one
- High autonomy, fast decisions, greenfield architecture
- Influence not just what we build — but how we work and who we hire next
🔧 You’ll Probably Touch…
- OpenAI, Claude, open-source models
- LangChain / AutoGen / or a roll-your-own agent layer
- Pinecone, Weaviate, Postgres, Supabase
- React/Next.js or equivalent for UI
- GCP, AWS, Vercel, or lightweight infra for fast iteration
Originally posted on Himalayas