Clinical Informatics Lead

Trudell Medical Group

10d•Remote

About The Position

Aetonix is a digital health company building a chronic care management platform for U.S. health systems, clinics, and ACOs. Our product has two faces: A mobile app that helps Medicare patients (65+) complete simple, guided check‑ins, and A desktop app that helps care teams know which patients need them most — and act. We are backed by Trudell Medical International (TMI), a Canadian-headquartered medical device company. We operate with patient capital and startup urgency. The next 6 months are about proving product-market fit with real clinical evidence in a category where fewer than 4% of eligible U.S. patients are currently receiving the care they are entitled to. This is a Full Time Remote opportunity based in Canada or the United States. Aetonix is looking for a hands-on clinical informatics leader to shape the clinical backbone of our multi-condition, respiratory-native care management platform. In this role, you'll own the critical translation of clinical best practice into the structured, computable logic that powers everything we build — converting established clinical guidelines into versioned digital care pathways, defining our clinical data model and terminology standards, and running the governance processes that keep our clinical content safe, evidence-based, and aligned with an evolving regulatory landscape. You'll also define the clinical ground truth that underpins and constrains our AI capabilities, ensuring that as the platform grows more intelligent, it stays grounded in sound clinical reasoning. This is a high-impact, cross-functional role: you'll report directly to the Chief Technology Officer, maintain a close working relationship with clinical leadership, and collaborate daily with product and engineering teams to bring clinical rigor directly into the heart of the platform. If you're energized by working at the intersection of clinical practice, data structure, and emerging AI technology — and want your expertise to directly shape a platform used in real-world respiratory care — we'd love to hear from you.

Requirements

Graduate degree in health, clinical, or biomedical informatics — or equivalent formal certification (e.g., nursing informatics board certification, clinical informatics subspecialty certification).
7+ years of progressive experience in clinical informatics, digital health, or health information technology.
Direct, hands-on experience translating clinical guidelines or protocols into structured, computable artifacts — care pathways, order sets, clinical decision support rules, or equivalent.
Working command of core clinical terminologies and standards, including ICD-10-CM, SNOMED CT, LOINC, and RxNorm.
Strong working knowledge of chronic disease management, particularly respiratory conditions such as COPD and asthma, along with common comorbidities (heart failure, hypertension, diabetes).
Practical familiarity with HL7 FHIR and experience supporting or preparing for EHR interoperability/integration work.

Nice To Haves

We recognize this field is moving fast and that deep AI/ML expertise in a clinical context is rare. If you are not quite there yet but are actively putting in the reps — reading about evals, building things outside of work, treating AI as a serious area of craft development — we want to hear from you. That orientation matters as much as the credential.

Responsibilities

Care pathway engineering. Translate clinical best-practice guidelines into structured, parameterized digital care pathways — starting with respiratory conditions like COPD and asthma and extending to common comorbidities (heart failure, hypertension, diabetes) as layered protocols on a shared engine, including patient goals, symptom checks, vitals, PROs, and educational content.
Parameter & data-capture design. Determine the optimal clinical parameters and alerting thresholds for each condition, and decide how each is best captured — self-reported, acoustic, rPPG, or via connected devices — balancing clinical value, patient burden, and data reliability, while designing how information flows to care teams so they can practice "top of license."
Clinical content governance. Own the clinical content lifecycle end-to-end: authoring standards, versioning, change control, and the review-and-approval workflow through which clinical leadership signs off before content reaches patients — keeping everything audit-ready and traceable.
Regulatory-aware architecture. Stay attuned to how pathway and knowledge-engineering decisions affect regulatory classification, supporting a modular architecture that isolates predictive/interpretive (SaMD) capabilities from non-diagnostic ones.
Clinical data model & terminology. Define and maintain the platform's canonical clinical data model and govern the standardized vocabularies (ICD-10-CM, SNOMED CT, LOINC, RxNorm, CPT/HCPCS) that keep data consistent, comparable, and shareable — including how it's structured for exchange via HL7 FHIR and USCDI in preparation for EHR integration.
AI clinical grounding. Define the clinical ground truth, acceptance criteria, and human-review checkpoints that keep AI features — care plan extraction, alerting, patient-facing content — clinically sound, safe, and appropriately gated, while serving as the clinical authority on release readiness and ongoing model monitoring.
Quality measures & evidence. Ensure the platform captures the data needed for HRRP, HEDIS, eCQMs, and UDS reporting, and structure clinical data to support the company's evidence program — validated endpoints, outcomes analysis, and study-grade data for formal HTA frameworks.
Embedded clinical partnership. Act as the clinical-domain partner to patient, care-team, and AI squads — translating clinical intent into engineering-ready requirements and surfacing technical constraints back to clinical stakeholders.