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Tier-2 brand, metro location, popular AI engineering title, broad skill requirements.
Core LLM and API skills transferable, but Nintex/Power Automate and Azure specifics raise domain sensitivity.
Multiple mandatory technical skills, LLM experience, Azure platform and leadership responsibilities increase filtering.
Own end-to-end AI-assisted migration platform architecture including AI-in-the-loop LLM output bounding and Azure cloud components.
Lead AI/ML strategy decisions covering build-vs-buy, model selection, fine-tuning vs prompting, and evaluation metrics definition.
Manage delivery, stakeholder coordination, and lead a 3–8 member AI/automation engineering team including risk and security management.
Proficiency in Node.js/TypeScript or Python and experience with XML/JSON parsing and rule engine or parser development.
Experience in AI/LLM engineering including prompt engineering, LLM API integration (Anthropic/OpenAI/Azure), and pipeline development (RAG/classification).
Experience in integration technologies like REST APIs, webhooks, Azure CLI/Azure AD authentication, and MCP server development.
Bachelor's degree in Engineering, Science, or MCA (B.E/B.Tech/M.Sc. Computers/MCA). Work Experience Required: Not explicitly mentioned in the JD.
Experienced in leading AI/automation engineering teams with capabilities in designing and delivering complex AI/LLM systems.
Strong technical ownership of cloud-based AI platforms with Azure services and ability to manage risk, security, and stakeholder expectations.
Skilled in full-stack AI software development from core parsing through AI integration to robust testing and quality assurance.