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Metro location, mid-level experience and known employer increase density, but niche GenAI specialization reduces it.
GenAI and Azure expertise is fairly transferable, yet requires specialized ML engineering background.
Explicit 6+ years plus mandatory GenAI, RAG, Azure, LangChain and production delivery raise strict filtering.
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Design and deploy Generative AI and Agentic AI solutions from concept through production, including multi-step agentic workflows.
Lead and mentor engineering teams; create production-ready architecture designs and technical documentation to support enterprise architecture discussions.
Collaborate with business teams and architects to solve complex problems, define enterprise AI standards, and contribute to knowledge graph and data pipeline strategies.
6+ years of software or AI/Machine Learning engineering experience.
Proven experience delivering Generative AI or Agentic AI solutions to production environment.
Strong Python development skills and hands-on experience with Microsoft Azure AI services.
Work Shift Timings: 2:00 PM - 11:00 PM IST.
Experienced in end-to-end Generative AI lifecycle, including Retrieval-Augmented Generation (RAG) and agent orchestration techniques.
Capable of translating complex business needs into scalable, secure AI solutions within an enterprise setting.
Has leadership experience mentoring engineers or leading AI projects, with familiarity of frameworks like LangChain or LangGraph.