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.
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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.