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Specialized GenAI skills lower competition, but metro location and broad stack increase applicant density.
Highly specialized GenAI, LLM fine-tuning and vector search require ML-specific backgrounds.
7+ years and mandatory GenAI stack and deployment experience enforce strict filtering.
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Design, develop, and orchestrate production-ready Generative AI applications using multi-agent systems and advanced RAG pipelines.
Integrate, fine-tune, and manage deployment of diverse LLMs (commercial and open-source) for scalable, high-performance backend services.
Optimize latency, cost, and reliability of GenAI workflows via prompt engineering, monitoring, and containerized deployment with Docker.
7+ years of experience building and deploying Generative AI applications in production.
Proficient in Python and AI frameworks such as LangChain, LlamaIndex, PyTorch, TensorFlow.
Experience with vector search, embedding models, advanced data retrieval, and local LLM hosting/quantization.
Familiarity with production-grade monitoring, API security, and CI/CD for ML deployment.
Deep expertise in building scalable GenAI backend systems using asynchronous Python and FastAPI.
Skilled in designing complex AI workflows involving multi-agent architectures and RAG technology.
Experienced in balancing model performance and operational cost through LLM integration and prompt engineering.