AI Quality Engineer

xCures Inc.

10d•$100,000 - $130,000•Remote

About The Position

xCures is seeking an AI Quality Engineer to ensure the scientific and regulatory scrutiny of its clinical extractors as the company scales. This role is responsible for the quality control that maintains the trustworthiness of extractors, leads regulatory alignment for client reliance on outputs, and translates extractor performance into clear, evidence-backed reporting. The AI Quality Engineer will collaborate with Data Science, Engineering, and Clinical Informatics to transform medical text into reliable, source-linked clinical data for use in real clinical decisions.

Requirements

Strong background in computational biology, bioinformatics, or a related life sciences discipline, whether through formal education or hands-on experience
Strong clinical knowledge across major disease areas, including diagnostic criteria, staging or severity classifications, and standard-of-care treatment patterns
Demonstrated experience with electronic medical records and the current healthcare data landscape, including Health Information Exchanges (HIE) and Qualified Health Information Networks (QHIN)
Demonstrated experience with structured clinical data and real-world data analysis
Strong grasp of data quality principles, data validation processes, and the ability to assess the provenance and limitations of real-world data
Proficiency in Python, R, or SQL for data manipulation and analysis
Ability to translate complex scientific concepts into clear, actionable findings for technical and non-technical audiences
Strong written and verbal communication skills
Proven ability to manage multiple complex, unrelated projects at once, with strong organization and time management
Comfort working remotely with virtual collaboration tools
Authorization to work in the United States

Nice To Haves

4+ years of relevant industry experience
Master's degree in computational biology, bioinformatics, or a life sciences discipline
Experience with medical coding ontologies (SNOMED, LOINC, RxNorm, OMOP)
Familiarity with version control (Git/GitHub) and collaborative code workflows
Comfort in a command-line environment and cloud development tools (AWS, GCP, or similar)
Experience defining or reporting quality and performance metrics for AI or data-extraction systems
Familiarity with de-identification (HIPAA Safe Harbor or Expert Determination) and clinical data governance

Responsibilities

Lead ongoing quality control of clinical extractor outputs, running systematic accuracy and consistency analyses across detection, data-set composition, and value extraction, and resolving discrepancies before they reach clients
Lead regulatory alignment for the extraction and validation program, keeping quality processes, methodology, and documentation consistent with applicable privacy, de-identification, and clinical-data standards
Lead client-facing performance reporting, translating validation metrics and extractor capabilities and limitations into clear, evidence-backed reports for client and internal audiences
Serve as an internal subject-matter expert for clinical domains, with an emphasis on oncology and real-world evidence, guiding the Data Science team on interpretation, clinical relevance, and the limits of current extraction methods
Partner with Data Science to prototype and refine extraction logic, inferred variables, normalization, and binning, contributing domain expertise on the nuances of medical text
Define and monitor clinical quality KPIs, track extractor performance drift over time, and recommend retraining or recalibration when the data warrants it
Work with Engineering and Clinical Informatics to ensure accurate export of structured clinical data into downstream formats such as FHIR bundles and CSV tables
Support data governance and dataset integrity, contributing to data-dictionary alignment, de-identification, and the quality of clinical datasets used for development and delivery
Serve as a clinical reviewer in internal quality reviews, client demos, and QA events, and support business development with feasibility analysis for prospective and current clients