Senior Full-Stack AI Engineer – DeepLaw

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