About
GitLaw builds tools that make legal work transparent and accessible. Our platform helps users collaborate on contracts, track changes, and use AI to summarize and modify documents. We’re a small team where engineers have a real impact on product decisions.
Position Overview
We are looking for a strong Python engineer to join our Chat Agent team. Your main focus will be developing and improving our AI agent: planning, reasoning, RAG pipelines, document integrations, evaluations, and LangChain/LangGraph workflows.
Note: We value strong software architecture and Python internals significantly more than experience with specific LLM frameworks. If you are a great engineer, we will teach you the AI parts.
Key Responsibilities
Core Engineering & Architecture (Primary)
- Design and maintain a strictly typed, asynchronous Python codebase (Python 3.13, uvloop).
- Ensure rigorous code quality using strict mypy typing, ruff, and comprehensive testing strategies.
- Contribute to performance tuning and reliability (async I/O, connection pooling, uvloop, caching).
Agent Development
- Build the state machines that drive agent behavior (using LangGraph logic).
- Integrate the agent with legal document workflows (drafting, editing, template search, analysis).
- Improve RAG pipelines (Vertex AI search, in-memory/FAISS-like stores) and context management.
Requirements
Technical Skills
- Expert-level knowledge of Python 3.10+ (specifically asyncio, typing system, and concurrency patterns).
- Experience building backend services (REST and/or gRPC) in production.
- Solid understanding of relational databases and SQL; experience with PostgreSQL is preferred.
- Experience with Git-based workflows and collaborative development.
- Comfortable working with Docker and containerized development environments.
Soft Skills
- Strong problem-solving and ownership mindset.
- Clear communication and ability to work asynchronously.
- Attention to detail and willingness to iterate.
Nice to Have
- Experience with Rust (we use Rust bindings for high-performance document processing).
- Familiarity with LangGraph or state-machine-based agent architectures.
- Knowledge of vector databases and RAG systems.
- Experience working with LLMs (OpenAI, Anthropic, etc.).
- Experience building chatbots or autonomous agents.
- Familiarity with GCP.
- Understanding of QA/Eval tools for LLM applications.
- Experience with monitoring and evaluating LLM outputs.
What We Offer
- Competitive salary and bonuses.
- Fully remote work and flexible hours.
- Growth opportunities and ownership of core agent features.
- A collaborative and practical engineering culture.