Genzeon

AI Product Builder | Healthcare AI Platform

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Product Builder in a Healthcare AI Platform, offering a remote position for over 6 months at a pay rate of "150K/year." Requires experience in AI projects, healthcare data familiarity, and skills in RAG, document AI, and systems thinking.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
May 27, 2026
πŸ•’ - Duration
More than 6 months
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🏝️ - Location
Remote
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Exton, PA
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🧠 - Skills detailed
#Alation #Classification #Hugging Face #AI (Artificial Intelligence) #API (Application Programming Interface) #Deployment #FHIR (Fast Healthcare Interoperability Resources) #CMS (Content Management System) #Langchain #Scala #"ETL (Extract #Transform #Load)" #GitHub #C++ #ML (Machine Learning)
Role description
AI Product Builder | Healthcare AI Platform Genzeon Corporation β€” Healthcare Division Exton, PA / Remote | 0–3 years | Full-time The short version: We use AI to process Medicare prior authorization documents β€” vision models, OCR, classification, RAG, clinical reasoning. 150K documents/year. You’ll own the product experience layer of that pipeline. You’ll design what happens when AI is confident,when it’s uncertain, and when it’s wrong. What you’ll do: Own the product experience across a multi-model AI pipeline (classification β†’extraction β†’ clinical QA β†’ decision) Design confidence thresholds, human review workflows, and escalation logic Work directly with ML engineers on model selection, prompt design, and architecture decisions Build feedback loops between clinical reviewers and AI performance Translate CMS/Medicare regulatory requirements into AI system behaviors What you need: At least one AI project you’ve built that other people used (we’ll ask what broke) Understanding that LLMs are probabilistic and what that means for product design Hands-on experience with one or more of: RAG, document AI, vision-language models,multi-agent systems Ability to read code, navigate a repo, and have a technical conversation with engineers Systems thinking β€” you care about what happens in the pipeline, not just the UI Strong signals: GitHub with AI projects β€” agents, RAG pipelines, fine-tuned models Open-source contributions (LangChain, LlamaIndex, Hugging Face, llama.cpp) AI hackathon participation Familiarity with healthcare data (FHIR, X12, HL7) Experience with on-prem GPU deployment, not just API calls