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Mid-level GenAI role in metros with strong brand and popular LLM skillset increases applicant competition.
GenAI and cloud skills are transferable across industries, though enterprise Azure and vector-search experience adds moderate specialization.
Explicit 5-8 years plus mandatory Python, GenAI, Azure, LangChain, and SQL increases filtering strictness.
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Design and develop Generative AI-powered applications including APIs, services, and orchestration using Python.
Implement RAG workflows, prompt engineering, and response evaluation for GenAI solutions.
Build and optimize backend services integrating with Azure components ensuring deployment, security, and scalability.
5 to 8 years of work experience in relevant AI or software engineering roles.
Advanced proficiency in Python programming, including API development and modular design.
Hands-on experience with Azure services such as App Services/Functions, Storage, and Key Vault.
Experience with Generative AI concepts including LLMs, prompt engineering, and GenAI application patterns.
Experienced in integrating ML/LLM workflows within production cloud environments, particularly Azure.
Strong SQL skills for data extraction, transformation, and validation in GenAI applications.
Familiar with Git version control workflows, CI/CD pipelines, and secure solution development for scalable enterprise applications.