AI Quality Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee continuous quality control of clinical extractor deliverables

• Conduct systematic analyses for accuracy and consistency in detection, dataset composition, and value extraction

• Address discrepancies prior to client delivery

• Spearhead regulatory alignment for extraction and validation initiatives

• Uphold quality processes, methodologies, and documentation in accordance with relevant privacy, de-identification, and clinical-data standards

• Lead performance reporting for clients

• Convert validation metrics and extractor capabilities and limitations into evidence-based reports

• Act as an internal subject-matter expert in clinical domains, particularly in oncology and real-world evidence

• Advise the Data Science team on interpretation, clinical significance, and extraction method limitations

• Collaborate with Data Science to prototype and enhance extraction logic, inferred variables, normalization, and binning

• Establish and monitor clinical quality KPIs

• Monitor extractor performance trends and suggest retraining or recalibration as needed

• Collaborate with Engineering and Clinical Informatics to ensure accurate export into FHIR bundles and CSV tables

• Support data governance and dataset integrity, including alignment with data dictionaries, de-identification, and clinical dataset quality

• Serve as a clinical reviewer during internal quality assessments, client demonstrations, and QA events

• Assist business development with feasibility analyses for both prospective and existing clients

⛳️ Requirements

• Strong foundation in computational biology, bioinformatics, or a related life sciences field through formal education or practical experience

• In-depth clinical knowledge across major disease areas, including diagnostic criteria, staging or severity classifications, and standard treatment protocols

• Familiarity with electronic medical records and the healthcare data ecosystem, including Health Information Exchanges (HIE) and Qualified Health Information Networks (QHIN)

• Experience with structured clinical data and real-world data analysis

• Solid understanding of data quality principles and validation processes

• Ability to evaluate the origin and limitations of real-world data

• Proficient in Python, R, or SQL for data analysis and manipulation

• Capability to translate complex scientific concepts into clear, actionable insights for both technical and non-technical audiences

• Excellent written and verbal communication skills

• Ability to juggle multiple complex, unrelated projects concurrently

• Strong organizational and time management skills

• Comfortable working remotely using virtual collaboration tools

• Must possess authorization to work in the United States

• 4+ years of relevant industry experience (preferred)

• Master’s degree in computational biology, bioinformatics, or a life sciences discipline (preferred)

• Experience with medical coding ontologies, such as SNOMED, LOINC, RxNorm, or OMOP (preferred)

• Familiarity with Git/GitHub and collaborative coding practices (preferred)

• Comfort with command-line interfaces and cloud development tools like AWS or GCP (preferred)

• Experience in defining or reporting quality and performance metrics for AI or data extraction systems (preferred)

• Understanding of de-identification and clinical data governance (preferred)

🏝️ 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