Senior Enterprise AI Enablement Engineer

MediQuant, LLC

North Olmsted (OH)

Hybrid

USD 120,000 - 180,000

Full time

12 days ago

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Job summary

MediQuant, Inc. is seeking an AI Enablement Engineer in Independence, OH, to lead senior-level AI/LLM initiatives across enterprise products.

You will evaluate platforms, design scalable AI workflows, and ensure secure handling of PHI/PII data while driving adoption and measurable improvements in implementation velocity. This role collaborates with rapid prototyping teams, architecture, and security to deliver production-ready AI capabilities, including governance and performance metrics across

Qualifications

  • Deep AI/LLM engineering knowledge and hands-on experience.
  • Security and privacy best practices for PHI/PII data in AI workflows.
  • Prompt engineering and orchestration frameworks (LangChain, vector search, semantic caching).
  • Strong communication and ability to mentor senior developers.

Responsibilities

  • Evaluate and design AI/LLM platform solutions for enterprise products.
  • Assess security posture, architecture fit, and total cost of ownership for AI tooling.
  • Collaborate with architecture to align AI solutions with enterprise data flows and security standards.
  • Lead AI enablement and workflow automation across delivery teams.
  • Document reference workflows and provide training to reduce adoption friction.
  • Document current-state data onboarding workflows and pain points for AI integration.
  • Develop governance guardrails for PHI/PII in AI sessions and pipelines.
  • Drive adoption metrics and provide enterprise-wide visibility to leadership.

Job description

MediQuant, Inc. is seeking an AI Enablement Engineer in Independence, OH, to lead senior-level AI/LLM initiatives across enterprise products.

You will evaluate platforms, design scalable AI workflows, and ensure secure handling of PHI/PII data while driving adoption and measurable improvements in implementation velocity. This role collaborates with rapid prototyping teams, architecture, and security to deliver production-ready AI capabilities, including governance and performance metrics across

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