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Niche GenAI expertise but metro location and attractive employer produce medium competition.
Specialized GenAI, agentic architecture, and vector DB skills limit cross-industry transferability.
Extensive mandatory GenAI frameworks, cloud, and agentic architecture skills enforce high shortlisting strictness.
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Design and develop enterprise Generative AI solutions leveraging cloud platforms including Azure and Amazon Bedrock.
Lead architecture and implementation of advanced AI systems such as Retrieval-Augmented Generation (RAG), multi-agent orchestration, and AI agents with tool-calling capabilities.
Mentor team members, troubleshoot complex AI workflows, and drive continuous improvements in AI solution quality and operational effectiveness.
Expertise in Generative AI frameworks and architectures including LangChain, LangGraph, Azure AI Foundry, and experience with RAG and Agentic AI systems.
Proficient in cloud application integration and deployment, specifically on Azure with DevOps tools like GitLab/GitHub and Azure Pipelines.
Strong programming skills in Python and experience with AI-related libraries (Pandas, NumPy).
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in designing scalable, cloud-native AI solutions with focus on enterprise deployment standards and responsible AI practices.
Comfortable leading AI architectural design, fine-tuning models, and implementing Human-in-the-Loop evaluation workflows for AI quality and governance.
Demonstrates strategic capability to align AI engineering best practices with business and technical objectives in a fast-paced technology services environment.