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Metro mid-level AI role with popular title but niche LLM/agent requirements.
Core ML/LLM skills are transferable, but healthcare data privacy and compliance increase domain specificity.
Explicit years, mandatory LLM experience, degree and specific tooling requirements make filters strict.
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Design, build, and maintain production-grade LLM-powered AI systems and agentic workflows for healthcare marketing intelligence products.
Develop robust retrieval-augmented generation (RAG) pipelines integrating diverse healthcare and campaign data with focus on latency, cost, and reliability.
Own scalable cloud deployment, MLOps/LLMOps practices, and evaluation frameworks ensuring safety, privacy, and compliance in handling healthcare data.
Bachelor's or higher in Computer Science, IT, Statistics, or related quantitative field from a Tier 1/2 institution.
2-8 years of AI/ML production systems experience, with at least 2 years on LLM-based or agentic AI applications.
Proficient in Python programming, software engineering best practices, and cloud-native deployment on AWS.
Experience with LLM/agent frameworks (e.g., LangChain, LlamaIndex), vector databases, prompt engineering, and compliance considerations for healthcare data.
Experienced in bridging advanced AI (LLMs, agents) with backend production systems in regulated, complex domains like healthcare.
Demonstrates strong product sense to translate ambiguous requirements into scalable AI subsystems with measurable business impact.
Skilled in building robust evaluation and monitoring pipelines, and communicating technical trade-offs to cross-functional stakeholders.