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You will design and build agentic AI systems for healthcare using the NeuroStack Agentic Operating System. You will work closely with clinical SMEs, healthcare operations experts, and compliance teams to deliver production-grade AI solutions across diagnostics, care coordination, clinical documentation, population health, and operational optimization. This role blends Generative AI, classical ML, and full-stack engineering in regulated environments.
Job Responsibility:
Design and implement agent-based AI workflows for healthcare use cases (clinical assistants, triage agents, care pathway optimization, RCM automation)
Build LLM-powered systems (RAG, tool-calling agents, multi-agent orchestration)
Develop classical ML models (risk scoring, prediction, clustering, anomaly detection)
Implement HIPAA aware AI architectures with auditability and traceability
Build full-stack applications (Python APIs, AI services, UI dashboards)
Integrate with EHRs, data lakes, and healthcare systems (FHIR/HL7 exposure preferred)
Collaborate with SMEs to translate medical workflows into agent logic
Deploy, monitor, and optimize AI systems in Azure
Requirements:
8–12+ years of experience in AI/ML and Software Engineering
Strong experience in Python-based AI systems
Hands-on experience with GenAI (LLMs, RAG, embeddings, prompt engineering)
Experience with traditional ML (classification, regression, NLP, time-series)