Job Description

Responsibilities

  • Leverage AI tools and frameworks not only for automation but as creative partners—experimenting with prompts, refining outputs, and integrating generative models into the development workflow.
  • Demonstrate critical evaluation of AI-generated results, ensuring quality, maintainability, and reliability.
  • Design, develop, and maintain production-grade software systems with senior-level code quality and architecture standards.
  • Lead the design, development, and deployment of 
    AI-enabled systems
    , including LLM-based agents and RAG pipelines.
  • Collaborate with cross-functional teams (PMs, data scientists, backend engineers) to define product scenarios and optimize AI workflows.
  • Architect scalable solutions using modern cloud platforms (Azure) and MLOps tools (MLFlow, Kubeflow, CI/CD).
  • Implement and optimize vector databases (e.g., FAISS, Pinecone, Qdrant) and retrieval systems for enterprise knowledge ...

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