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Specialized GenAI role with broad skills at a known analytics firm, moderate competition.
Requires niche GenAI, LLMOps, and Azure Databricks expertise, limiting cross-industry portability.
Extensive mandatory GenAI frameworks, Azure Databricks, and LLMOps skills enforce strict shortlisting.
Design, develop, and deliver end-to-end scalable Generative AI solutions using Large Language Models and related frameworks with measurable business impact.
Own solution success metrics including adoption, accuracy, latency, cost efficiency, and drive improvements across AI systems lifecycle.
Lead architecture design of advanced LLM applications (e.g., RAG pipelines, agentic workflows), oversee reusable AI component development, ensure robustness and responsible AI governance.
Experience with SaaS and Open-Source LLM frameworks (e.g., LangChain, Azure OpenAI, CrewAI).
Proficiency in Python and FastAPI, with cloud experience primarily in Azure DevOps and Azure AI services.
Hands-on knowledge of advanced retrieval-augmented generation (RAG) techniques and agentic Generative AI frameworks.
Work Experience Required: Not explicitly mentioned in the JD.
Comfortable owning end-to-end AI projects from design through deployment with minimal supervision in a fast-evolving GenAI domain.
Experienced with integrating AI solutions into business systems while influencing cross-functional stakeholders and roadmaps.
Strong in building modular, production-grade AI infrastructure focused on trade-offs (latency, cost, accuracy) and governance for safe, scalable LLM deployments.