Backend Engineer - Python AI
Summary
Backend engineer building and scaling the AI platform's infrastructure — agentic systems, memory layers, RAG pipelines, and ontologies in production-grade asynchronous Python (FastAPI, LangGraph/LangChain) — so the AI can act as a co-pilot for logistics professionals.
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.