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Niche GenAI skillset, metro location, and unspecified experience produce moderate candidate competition.
Highly specialized LLM, RAG, and Databricks expertise reduces cross-industry transferability.
Extensive mandatory LLM, RAG, Databricks, and productionization skills imply strict technical filtering.
Design, develop, and deliver production-grade Generative AI solutions leveraging Large Language Models (LLMs) and advanced RAG systems with end-to-end ownership.
Build reusable AI frameworks, components, and maintain high code quality through reviews and mentor junior team members.
Collaborate cross-functionally to align AI initiatives with business impact metrics such as adoption, accuracy, latency, and cost efficiency.
Experience with Generative AI tools and frameworks including LangChain, LlamaIndex, Azure OpenAI, GPT-3.5/4, and one agentic AI framework (e.g., AutoGen, LangGraph).
Proficiency in Python, FastAPI, and Azure cloud services including Azure DevOps, Azure Databricks, and Azure Function Apps.
Familiarity with advanced Retrieval-Augmented Generation systems and classical NLP techniques such as text classification, conversational AI, and Named Entity Recognition.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in architecting scalable, modular AI systems balancing trade-offs between latency, cost, and accuracy in a cloud/Azure environment.
Strong operational focus on code quality, reusable components, and AI system reliability including hallucination mitigation and bias governance.
Able to translate ambiguous business problems into structured AI solutions with measurable KPIs and engage directly with business and technical stakeholders.