Backend Engineer - Python AI
Summary
Build and scale Python backend infrastructure and AI agentic systems (RAG pipelines, long-term memory layers, knowledge graphs) that act as a co-pilot for logistics professionals. Core stack: async Python with FastAPI/Pydantic, LangGraph/DSPy/LangChain, vector databases, LLMs, and GCP.
Overview
We are looking for an engineer to help scale our backend infrastructure and deepen our agentic capabilities. This individual will not just be wrapping APIs; they will be building the memory layers, RAG pipelines, and ontological structures that allow our AI to serve as a true co-pilot for logistics professionals.
Technical Requirements
- Expert Python Engineering: Production-grade, asynchronous Python (FastAPI/Pydantic) with a focus on performance and scalability.
- Agentic Frameworks & Reasoning: Hands-on experience with LangGraph, DSPy, or LangChain. Must understand state management, agent loops, and reliable tool-calling. Experience with evaluations is a significant bonus.
- Knowledge Graphs & Ontologies: Experience building or working with ontologies.
- Advanced Memory Management: Implementation of \"long-term memory\" using vector databases and schemas to maintain context over long horizons.
- RAG & LLMs: Experience with RAG optimization (reranking, query transformation) and/or fine-tuning LLMs for domain-specific reasoning.
- Experience with GCP is preferred
- Understands Secure SDLC practices
Core Competencies
- Quick learner with high agency.
- A \"product engineer\" mindset.
- Comfort with ambiguity and a sense of extreme ownership.
- Experience working in a fast paced environment.