Python Engineer

Resource Logistics, Inc.

  • San Jose, CA
  • 30+ days ago

    Highlights

    Agent Logic Integration: Clienthitect the backend systems that power our AI agents, managing long-running tasks, state persistence, and seamless communication between LLMs and our core services. Scalable API Development: Design, build, and maintain robust, high-throughput APIs (FastAPI, Django, or Flask) capable of handling millions of requests.

    Numbers & Facts

    LocationSan Jose, CA
    IndustryMedical Devices and Supplies
    Company Size500 to 999 employees

    Description

    Python Engineer
    San Jose, CA, USA

    Local profiles only followed by in-person Interview at onsite in Santa Clara, CA client office


    Role Overview:
    We are looking for a Python Developer to build the backbone of our platform. You will be responsible for creating high-performance APIs, integrating advanced AI agent logic, and ensuring our infrastructure remains rock-solid as we scale. If you enjoy solving complex Clienthitectural puzzles and want to work at the intersection of traditional backend engineering and AI

    Core Responsibilities
    Scalable API Development: Design, build, and maintain robust, high-throughput APIs (FastAPI, Django, or Flask) capable of handling millions of requests.
    Agent Logic Integration: Clienthitect the backend systems that power our AI agents, managing long-running tasks, state persistence, and seamless communication between LLMs and our core services.
    Authentication & Security: Implement and manage secure identity protocols (OAuth2, JWT, OpenID Connect) to protect user data and internal endpoints.
    Routing & Orchestration: Design efficient request routing and service communication patterns using tools like API Gateways, or Service Meshes.

    Required Technical Skills
    Language: Expert-level proficiency in Python (3.10+ preferred).
    Frameworks: Deep experience with FastAPI, Django
    AI Tooling: Familiarity with LangChain, Llama Index, or similar frameworks for agentic workflows.
    Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate).
    Infrastructure: Proficiency with Docker, AWS/GCP, and asynchronous task queues

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