AI Quality Engineer

xCures Inc.

. Lead ongoing quality control of clinical extractor outputs .

Posted 9/20/2026full-timeRemote • United StatesMid-LevelSenior💰 $100,000 - $130,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in clinical data quality control, validation processes, and regulatory alignment, with a strong foundation in computational biology and bioinformatics. Proficient in data manipulation using Python, R, or SQL, and capable of translating complex scientific concepts for diverse audiences.

Highest-signal resume keywords

Clinical Data Quality ControlData Manipulation Using Python, R, Or SQLRegulatory Alignment For Extraction ProgramsExperience With Electronic Medical RecordsStrong Clinical Knowledge Across Major Disease Areas

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Computational BiologyBioinformaticsData Validation ProcessesData Quality PrinciplesStructured Clinical Data AnalysisReal-World Data AnalysisMedical Coding OntologiesQuality And Performance Metrics ReportingData GovernanceClinical Dataset Quality

Soft Skills

Strong Written And Verbal CommunicationOrganization And Time ManagementAbility To Manage Multiple Projects

Tools & Technologies

Electronic Medical RecordsHealth Information ExchangesGit/GitHubAWSGCP

Industry Keywords

Clinical DomainsOncologyReal-World EvidenceDe-IdentificationClinical Data Standards

Tech Stack

Tools & technologies

AWSCloudGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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