
51 - 200 employees
Founded 2018
đ„ Healthcare
đ€ Artificial Intelligence
âïž SaaS
Healthcare âą Artificial Intelligence âą SaaS
xCures is a healthcare AI company that provides a Clinical Clarity Engine to retrieve, assemble, and structure fragmented medical records into decision-ready, source-linked clinical data. Its productsâEvidence Grade Data, Automated Patient History, and Decision-Ready Checklistsâextract and validate clinical information at scale, delivering verifiable outputs via summaries, dashboards, APIs, and export feeds for healthcare teams and partners. xCures is B2B-focused, serving providers, diagnostics groups, value-based care organizations, and channel partners; it emphasizes traceability and validation (peer-reviewed research, high extraction accuracy, and HITRUST certification) and processes medical records at large scale to accelerate prior authorization, chart review, quality reporting, and other clinical and operational workflows.
đ September 20
đșđž United States â Remote
đ” $100k - $130k / year
â° Full Time
đĄ Mid-level
đ Senior
đ§ QA Engineer (Quality Assurance)
đ» Ghost score 10%
Where this job comes from
Posted on xCures Inc.'s careers page, not through a job board
First seen by Remote Rocketship September 20
Still open on xCures Inc.'s site. Checked 2 hours ago.

51 - 200 employees
Founded 2018
đ„ Healthcare
đ€ Artificial Intelligence
âïž SaaS
Healthcare âą Artificial Intelligence âą SaaS
xCures is a healthcare AI company that provides a Clinical Clarity Engine to retrieve, assemble, and structure fragmented medical records into decision-ready, source-linked clinical data. Its productsâEvidence Grade Data, Automated Patient History, and Decision-Ready Checklistsâextract and validate clinical information at scale, delivering verifiable outputs via summaries, dashboards, APIs, and export feeds for healthcare teams and partners. xCures is B2B-focused, serving providers, diagnostics groups, value-based care organizations, and channel partners; it emphasizes traceability and validation (peer-reviewed research, high extraction accuracy, and HITRUST certification) and processes medical records at large scale to accelerate prior authorization, chart review, quality reporting, and other clinical and operational workflows.
âą Lead ongoing quality control of clinical extractor outputs âą Run systematic accuracy and consistency analyses across detection, dataset composition, and value extraction âą Resolve discrepancies before they reach clients âą Lead regulatory alignment for extraction and validation programs âą Maintain quality processes, methodology, and documentation consistent with applicable privacy, de-identification, and clinical-data standards âą Lead client-facing performance reporting âą Translate validation metrics and extractor capabilities and limitations into evidence-backed reports âą Serve as an internal subject-matter expert for clinical domains, especially oncology and real-world evidence âą Guide the Data Science team on interpretation, clinical relevance, and extraction-method limitations âą Partner with Data Science to prototype and refine extraction logic, inferred variables, normalization, and binning âą Define and monitor clinical quality KPIs âą Track extractor performance drift and recommend retraining or recalibration âą Work with Engineering and Clinical Informatics to ensure accurate export into FHIR bundles and CSV tables âą Support data governance and dataset integrity, including data-dictionary alignment, de-identification, and clinical dataset quality âą Serve as a clinical reviewer in internal quality reviews, client demos, and QA events âą Support business development with feasibility analysis for prospective and current clients
âą Strong background in computational biology, bioinformatics, or a related life sciences discipline through formal education or hands-on experience âą Strong clinical knowledge across major disease areas, including diagnostic criteria, staging or severity classifications, and standard-of-care treatment patterns âą Experience with electronic medical records and the healthcare data landscape, including Health Information Exchanges (HIE) and Qualified Health Information Networks (QHIN) âą Experience with structured clinical data and real-world data analysis âą Strong grasp of data quality principles and data validation processes âą Ability to assess the provenance and limitations of real-world data âą Proficiency in Python, R, or SQL for data manipulation and analysis âą Ability to translate complex scientific concepts into clear, actionable findings for technical and non-technical audiences âą Strong written and verbal communication skills âą Ability to manage multiple complex, unrelated projects simultaneously âą Strong organization and time management âą Comfort working remotely with virtual collaboration tools âą Must already have authorization to work in the United States âą 4+ years of relevant industry experience (bonus) âą Master's degree in computational biology, bioinformatics, or a life sciences discipline (bonus) âą Experience with medical coding ontologies, including SNOMED, LOINC, RxNorm, or OMOP (bonus) âą Familiarity with Git/GitHub and collaborative code workflows (bonus) âą Comfort with command-line environments and cloud development tools such as AWS or GCP (bonus) âą Experience defining or reporting quality and performance metrics for AI or data-extraction systems (bonus) âą Familiarity with de-identification and clinical data governance (bonus)
âą Remote-first work environment âą Paid time off âą 13 company holidays âą Equity package âą Paid parental leave âą Medical, vision, and dental insurance âą Employer HSA contribution âą Employer 401(k) match âą Short-term disability, long-term disability, life insurance, and critical illness plans âą Employee assistance program âą Adoption assistance âą Company offsites âą Monthly internet allowance âą Professional development funds
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