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Niche LLM and Azure AI Foundry expertise reduces candidate pool despite metro and mid-level demand.
Specialized cloud-native LLM, Azure, and vector DB skills moderately limit cross-industry portability.
Explicit 4–6 years plus mandatory Azure, Python, vector DBs, and RAG expertise makes filters highly strict.
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Own end-to-end design, development, deployment, and operational support of cloud-native AI multi-agent systems and advanced Retrieval-Augmented Generation (RAG) pipelines on Azure using Azure AI Foundry.
Leverage GitHub Copilot to accelerate development and maintain production-grade AI agents ensuring runtime stability and optimized performance.
Mentor and train internal engineering team on AI best practices, cloud-native AI development, and effective use of AI tooling.
4 to 6 years of professional software development experience with focus on cloud-native AI/ML engineering.
Strong Python programming skills including OOP, asynchronous programming, and clean code principles.
Hands-on experience with Azure Cloud Services and Azure AI Foundry for AI model deployment and management.
Experience with AI orchestration frameworks (e.g., LangChain, AutoGen) and vector databases (e.g., Azure AI Search, Pinecone).
Experienced independent individual contributor capable of managing AI products from concept through live production support with minimal supervision.
Proficient in architecting and building scalable multi-agent AI systems and advanced RAG pipelines on Azure Cloud.
Skilled mentor and communicator comfortable leading technical training and knowledge sharing within engineering teams.