Experienced LangChain Developer for AI SaaS
Budget: $30 – $250 USD
We're looking for an experienced LangChain/LangGraph developer to improve our existing multi-agent AI system that powers a customer-communication SaaS platform (WhatsApp, Instagram, web channels) for SMEs.
The system is already in production — built on LangGraph with Gemini Flash, including a RAG pipeline, tool binding, and structured output — but we're hitting issues and want professional support in these areas:
Inconsistencies/bugs in multi-agent orchestration flows
Memory management issues (conversation history, context propagation, session-based state)
Improving tool binding and deterministic RAG retrieval nodes
Hallucination prevention, especially in critical confirmation flows
General architecture review and best-practice recommendations
Requirements:
Production-level experience with LangChain and LangGraph (verifiable projects/references)
Strong understanding of multi-agent system design and state/memory management
Experience with structured output (Pydantic) and tool calling
Solid Python, async/await, and event-driven architecture knowledge
Gemini API experience preferred (OpenAI/Anthropic API experience also fine)
Good communicator, comfortable with code review, documents work clearly
Engagement: We can start with a paid audit/consultation to review the existing codebase and diagnose issues, then continue hourly or project-based depending on fit.
Note: NDA will be required; codebase access will be provided.
The system is already in production — built on LangGraph with Gemini Flash, including a RAG pipeline, tool binding, and structured output — but we're hitting issues and want professional support in these areas:
Inconsistencies/bugs in multi-agent orchestration flows
Memory management issues (conversation history, context propagation, session-based state)
Improving tool binding and deterministic RAG retrieval nodes
Hallucination prevention, especially in critical confirmation flows
General architecture review and best-practice recommendations
Requirements:
Production-level experience with LangChain and LangGraph (verifiable projects/references)
Strong understanding of multi-agent system design and state/memory management
Experience with structured output (Pydantic) and tool calling
Solid Python, async/await, and event-driven architecture knowledge
Gemini API experience preferred (OpenAI/Anthropic API experience also fine)
Good communicator, comfortable with code review, documents work clearly
Engagement: We can start with a paid audit/consultation to review the existing codebase and diagnose issues, then continue hourly or project-based depending on fit.
Note: NDA will be required; codebase access will be provided.