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Specialized LLM, Azure, and parsing skills plus lead title narrow the candidate pool, but AI roles remain sought-after.
Core LLM and engineering skills are transferable, but Nintex/Power Automate and Azure integration add moderate domain specificity.
Many mandatory specialized skills (LLM integration, Azure, parsing, eval harnesses) and leadership expectations create strict filters.
Own end-to-end architecture and delivery of AI-assisted migration platform including Azure cloud components and AI-in-the-loop systems.
Drive AI/ML strategy decisions on build-vs-buy, model selection, fine-tuning, and evaluation metrics for fidelity and gap analysis.
Lead and mentor a 3–8 member AI/automation engineering team; manage stakeholder engagement, risk, rollback strategies, and security reviews.
Bachelor's (B.E/B.Tech) or Master's (M.Sc. Computers/MCA) degree in computer science or related field.
Experience leading small-to-mid AI/automation engineering teams (3–8 developers).
Technical expertise in Node.js/TypeScript or Python with XML/JSON parsing, AI/LLM integration, Azure cloud architecture, and AI-in-the-loop system design.
Work Experience Required: Not explicitly mentioned in the JD.
Strong background in architecting and delivering complex AI/LLM-based automation platforms with Azure cloud expertise.
Proven experience in defining and implementing AI/ML strategies including model evaluation, cost/latency trade-offs, and fidelity scoring.
Ability to manage client stakeholder interactions, triage escalations, and lead cross-disciplinary AI and classical engineering teams.