AI Quality Engineer
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Job Description
AI Quality Engineer validating xCures’ clinical data extraction platform for healthcare decision-making. Leading quality control, regulatory alignment, performance reporting, and clinical data governance.
Responsibilities:
- Lead ongoing quality control of clinical extractor outputs
- Run systematic accuracy and consistency analyses across detection, dataset composition, and value extraction
- Resolve discrepancies before they reach clients
- Lead regulatory alignment for extraction and validation programs
- Maintain quality processes, methodology, and documentation consistent with applicable privacy, de-identification, and clinical-data standards
- Lead client-facing performance reporting
- Translate validation metrics and extractor capabilities and limitations into evidence-backed reports
- Serve as an internal subject-matter expert for clinical domains, especially oncology and real-world evidence
- Guide the Data Science team on interpretation, clinical relevance, and extraction-method limitations
- Partner with Data Science to prototype and refine extraction logic, inferred variables, normalization, and binning
- Define and monitor clinical quality KPIs
- Track extractor performance drift and recommend retraining or recalibration
- Work with Engineering and Clinical Informatics to ensure accurate export into FHIR bundles and CSV tables
- Support data governance and dataset integrity, including data-dictionary alignment, de-identification, and clinical dataset quality
- Serve as a clinical reviewer in internal quality reviews, client demos, and QA events
- Support business development with feasibility analysis for prospective and current clients
Requirements:
- Strong background in computational biology, bioinformatics, or a related life sciences discipline 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
- Experience with electronic medical records and the healthcare data landscape, including Health Information Exchanges (HIE) and Qualified Health Information Networks (QHIN)
- Experience with structured clinical data and real-world data analysis
- Strong grasp of data quality principles and data validation processes
- 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
- Ability to manage multiple complex, unrelated projects simultaneously
- Strong organization and time management
- Comfort working remotely with virtual collaboration tools
- Must already have authorization to work in the United States
- 4+ years of relevant industry experience (bonus)
- Master's degree in computational biology, bioinformatics, or a life sciences discipline (bonus)
- Experience with medical coding ontologies, including SNOMED, LOINC, RxNorm, or OMOP (bonus)
- Familiarity with Git/GitHub and collaborative code workflows (bonus)
- Comfort with command-line environments and cloud development tools such as AWS or GCP (bonus)
- Experience defining or reporting quality and performance metrics for AI or data-extraction systems (bonus)
- Familiarity with de-identification and clinical data governance (bonus)
Benefits:
- Remote-first work environment
- Paid time off
- 13 company holidays
- Equity package
- Paid parental leave
- Medical, vision, and dental insurance
- Employer HSA contribution
- Employer 401(k) match
- Short-term disability, long-term disability, life insurance, and critical illness plans
- Employee assistance program
- Adoption assistance
- Company offsites
- Monthly internet allowance
- Professional development funds
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