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Mid-level GenAI role in metro with broad in-demand skills increases applicant competition.
Requires deep LLM and RAG experience, making cross-industry transfers difficult without similar GenAI background.
Explicit years, mandatory Generative AI and toolchain requirements make screening highly selective.
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Design, develop, and deploy production-grade Generative AI applications leveraging LLMs, RAG, and Agentic AI frameworks.
Build AI-powered conversational assistants, chatbots, document intelligence platforms, and copilots using tools like LangChain, LangGraph, and integration with models from OpenAI, Azure, Claude, and others.
Develop backend APIs and scalable cloud-deployed AI services with monitoring, CI/CD pipelines, and mentor junior engineers.
5–8 years of overall software development experience.
3+ years of hands-on experience in Generative AI / LLM application development.
Proficiency in Python and frameworks like FastAPI for backend development.
Experience with cloud platforms such as Azure, AWS, or GCP, and containerization using Docker/Kubernetes.
Experienced in end-to-end GenAI product development from backend APIs to AI orchestration and deployment in cloud environments.
Comfortable working collaboratively with AI Architects, Data Scientists, and Product Teams in Agile settings.
Skilled in implementing sophisticated retrieval and agentic AI workflows optimizing for production-scale performance and reliability.