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Mid-level, generalist AI engineering role with broad LLM and production requirements in metro increases applicant competition.
Requires ML/AI specialization plus healthcare and scientific data context, moderately limiting cross-industry transferability.
Explicit 5+ years and mandatory production ML, LLM, cloud, security, and observability requirements enforce strict filters.
Design, develop, and maintain end-to-end AI-powered applications involving large language models, agentic AI solutions, and machine learning lifecycle engineering.
Engineer secure, scalable AI services and integrate enterprise data sources, APIs, and business systems into automated workflows and products.
Own production operations including deployment, monitoring, incident response, performance optimization, and continuous improvement of AI services.
Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field (Master's preferred).
5+ years professional experience in software, data, or ML engineering with hands-on delivery of AI/ML applications in production.
Strong proficiency in Python; experience with ML lifecycle activities and building LLM or agentic AI applications.
Experience with cloud-native or enterprise platforms, production engineering practices, modern data technologies, and design for security, scalability, and reliability.
Experienced AI/ML engineer capable of translating ambiguous scientific or business problems into measurable production-ready AI solutions.
Skilled in building and orchestrating complex AI workflows including LLM prompt design, tool integration, and human-in-the-loop controls.
Experienced in operating secure, observable, and reliable AI services within enterprise cloud or data platforms, collaborating across multidisciplinary teams.