Remote Clinical Systems Analyst for AI Training

Alignerr Corp.; Cambridge; On-site; GBP 55,000 - 110,000; Part time

Benefits offered by this job

Fully remote

Flexible schedule

Contract-based work

Job summary

Alignerr is seeking experienced Clinical Systems Analysts to apply real-world healthcare IT knowledge to AI training. You will evaluate AI responses related to EHR workflows and clinical systems, providing expert feedback.

This remote hourly contract offers flexible hours (10–40 per week) and the chance to work asynchronously with top AI researchers, while leveraging HL7 and FHIR standards to ensure interoperability and accuracy in AI reasoning for healthcare technology.

Qualifications

• Experienced in supporting or administering healthcare IT systems — EHRs, clinical applications, or hospital infrastructure.
• Strong ability to troubleshoot complex healthcare IT environments and workflows.
• Ability to provide structured, actionable feedback to AI teams.

Responsibilities

• Apply clinical systems expertise to evaluate AI-generated responses related to healthcare IT, EHR workflows, and system troubleshooting.
• Review and assess AI outputs for technical accuracy, clinical relevance, and practical usefulness.
• Identify gaps, errors, or weaknesses in how AI handles clinical systems scenarios and provide constructive feedback.
• Work independently and asynchronously on your own schedule.

Skills

Healthcare IT systems

EHR platforms

Clinical workflows

Technical troubleshooting

Clear feedback communication

Self-motivated / independent

Tools

HL7

FHIR

Interoperability standards

Job description

Alignerr is seeking experienced Clinical Systems Analysts to apply real-world healthcare IT knowledge to AI training. You will evaluate AI responses related to EHR workflows and clinical systems, providing expert feedback.

This remote hourly contract offers flexible hours (10–40 per week) and the chance to work asynchronously with top AI researchers, while leveraging HL7 and FHIR standards to ensure interoperability and accuracy in AI reasoning for healthcare technology.