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Metro location and known employer, but niche LLM/agent expertise reduces applicant density.
Medium because AI/LLM skills transfer widely, but Nintex/PowerAutomate and migration context add domain specificity.
High due to mandatory LLM, parsing, Azure architecture, and leadership responsibilities.
Own the end-to-end architecture and delivery of AI-assisted migration platform including AI-in-the-loop LLM output bounding and Azure cloud services.
Drive AI/ML strategy decisions such as build-vs-buy, model selection, fine-tuning vs prompting, and define evaluation metrics (fidelity scoring, gap analysis).
Lead and mentor a 3–8 person AI/automation engineering team; manage stakeholder relationships, scope feasibility vs production, data requirements, as well as risk, rollback, and security reviews.
Bachelor's degree in Engineering (B.E/B.Tech), M.Sc. in Computer Science, or MCA.
Experience leading AI/automation teams (3-8 developers) and managing AI/ML projects with client-facing delivery.
Technical skills: Node.js/TypeScript or Python, XML/JSON parsing, prompt engineering, LLM API integration (Anthropic/OpenAI/Azure OpenAI), Azure cloud architecture (App Services, Functions, Key Vault, Azure AD).
Work Experience Required: Not explicitly mentioned in the JD.
Technical leader comfortable with multi-stage AI coding architecture and AI-in-the-loop systems on Azure cloud platforms.
Experienced in defining AI/ML strategy including cost and latency tradeoffs, evaluation metric frameworks for generative AI.
Skilled in stakeholder management, risk and compliance handling (migration risk, security review), and mentoring cross-disciplinary engineering teams.