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Mid-level AI role, metro hiring, broad skillset and recognized employer increase candidate competition.
Specialized AI infrastructure skills are moderately transferable across industries due to cloud and integration focus.
Explicit 3–6 years plus mandatory Azure, RAG, vector DB and integration skills increases filter strictness.
Own implementation, deployment, and operational support of AI infrastructure including RAG pipelines, vector databases, APIs, and enterprise integrations.
Manage deployment and monitoring of AI solutions in Azure, ensuring scalability, performance, security, and cost efficiency.
Collaborate with AI Developers and product teams on design, support procedures, and governance compliance to maintain reliable AI production environments.
3-6 years of engineering experience including 1-3 years with AI/Generative AI solutions in a business setting.
Bachelor's degree in Computer Science, Engineering, IT, Data Science, Mathematics, or related field (or equivalent practical experience).
Proficient in Python, SQL, REST APIs, Azure cloud services, Azure OpenAI or OpenAI APIs, vector search, embeddings, and CI/CD pipelines.
Experience developing and supporting cloud-based AI integrations and backend services with exposure to Microsoft 365, SharePoint, Teams, and ERP system integrations.
Experienced in building and maintaining scalable, secure AI infrastructure for enterprise-scale deployments in Azure environments.
Comfortable working in an Agile, cross-functional team with focus on stable operational support and continuous improvement of AI solutions.
Technically proficient with strong backend and cloud integration skills, capable of handling AI solution technical foundation independently.