AI-Native Full Stack Software Engineer

AI-Native Full Stack Software Engineer at MINE Type: Senior Contractor (hourly, contract-to-hire) What MINE Is MINE automates chronic care billing compliance for independent metabolic practices. We ingest clinical and patient data from multiple sources, process it through an AI layer, and generate audit-ready billing documentation. We are building V1.0 now and need an engineer who designs AI-native systems from the ground up, not traditional software with AI bolted on afterward. What You Will Own Build the data integration layer: structured data pull from EHR systems and a patient-facing app into our core platform Build the device data pipeline: wearable and chronic care monitoring device data (glucose monitors, smart scales, blood pressure cuffs) ingested and normalized via a third-party aggregator API Build the AI documentation workflow: structured clinical data processed through an LLM layer, mapped to billing compliance criteria, surfacing correct billing categories with supporting documentation Build the document annotation workflow: source billing templates annotated with AI-processed patient data to produce clinician-ready outputs Operate within the HIPAA-compliant infrastructure established by Role 1 What Success Looks Like A fully operational documentation pipeline; from raw patient and device data in - to a pre-filled, evidence-linked billing document out - that a clinician can review, edit, and sign. Every output is traceable to source data. No clinical claim passes to sign-off without a supporting evidence link. Technical Standards Outputs must be audit-ready under post-payment review. PHI never touches logs or non-PHI stores. Eligibility logic is deterministic, the LLM handles narrative synthesis and data extraction only, never compliance decisions. Clinician sign-off is required before any document is finalized; nothing auto-submits. Required 3+ years full stack engineering experience Production AI pipeline experience: structured input → LLM processing → structured output → downstream action 6-month contract availability with milestone-based delivery Preferred Healthcare data experience: EHR integrations, billing workflows, or clinical documentation FHIR integration experience Document processing experience: extraction, annotation, structured output generation Experience with device or wearables data pipelines Regulated data environment experience: healthcare preferred, fintech or legal acceptable Engagement Hourly contract with performance incentives. 6-month initial scope with milestone-based checkpoints. Structured FTE conversion path with equity available for the right candidate. Application filter: Describe the most relevant AI pipeline you've built. What was the input, what did the model do, and what was the output?