Python AI Developer

Excellent opportunity to work REMOTELY with a U.S.-based company. Candidates living in Mexico, Argentina, or Brazil are welcome to apply.

About the Company

Bydrec, Inc. is a California-based company that connects top Tech talent from Latin America with U.S. companies looking to expand their development teams. Learn more at bydrec.com.

About the Role

We are looking for a Python AI Developer to help scale backend infrastructure and expand advanced AI capabilities for a fast-growing technology environment.

This role goes beyond traditional API development. The engineer will be responsible for building AI-powered systems that support intelligent decision-making for logistics professionals, including memory architectures, retrieval pipelines, and agent-based reasoning frameworks.

The ideal candidate has strong experience working with Python-based AI infrastructure, agentic frameworks, retrieval-augmented generation (RAG), and modern LLM systems. This role requires someone comfortable designing scalable architectures and working in fast-moving environments where ownership and initiative are highly valued.

• Design and develop scalable backend systems using Python with a strong focus on performance and asynchronous processing.
• Build and maintain AI infrastructure including memory layers, RAG pipelines, and reasoning workflows.
• Develop systems that enable AI agents to interact with tools, knowledge graphs, and external data sources.
• Design and implement long-term memory architectures using vector databases and schema-driven context management.
• Optimize and improve retrieval pipelines for LLM-based applications, including query transformation and reranking strategies.
• Collaborate with cross-functional teams to design scalable AI architectures and deploy production-ready solutions.
• Follow secure software development lifecycle (Secure SDLC) practices.

• Strong experience developing production applications using Python.
• Experience building scalable APIs and backend systems using FastAPI and Pydantic.
• Hands-on experience working with AI agent frameworks such as LangGraph, DSPy, or LangChain.
• Understanding of agent loops, tool-calling, and state management for AI agents.
• Experience implementing RAG (Retrieval-Augmented Generation) pipelines.
• Experience working with vector databases and long-term memory architectures for LLM applications.
• Experience working with knowledge graphs or ontologies.
• Strong understanding of performance optimization and scalable backend architectures.
• Advanced English communication skills.

• Experience optimizing LLM pipelines for domain-specific reasoning.
• Experience performing evaluation and testing of AI systems.
• Experience working with Google Cloud Platform (GCP).
• Experience building systems in high-growth or fast-paced startup environments.