Application Implementation Engineer – AI Implementation

This is a fully remote position, open to applicants in North Carolina.

📋 Description

• Oversee the technical evaluation, validation, implementation, integration, and clinical adoption of third-party clinical AI solutions.

• Install, configure, and maintain clinical AI software in sandbox, edge server, on-premise, and cloud environments.

• Set up DICOM routing, HL7 messaging, and de-identification workflows for images and reports.

• Design and conduct structured AI validation studies using relevant metrics such as sensitivity, specificity, discrepancy rates, and clinical/workflow impact.

• Create LLM/NLP-based frameworks to compare AI outputs with the ground truth established by radiologists.

• Develop Lumexa's reusable clinical AI validation playbook and automated evaluation tools.

• Write evidence-based go/no-go recommendations for the AI Governance Council, which includes risk assessment and deployment scope.

• Collaborate with clinical leadership to define ground truth, acceptance thresholds, workflow fit, and clinical priorities.

• Convert validated AI capabilities into deployment-ready integration designs tailored for radiologist workflows.

• Analyze current and future-state workflows, identifying workflow risks, change-management considerations, and barriers to adoption.

• Assist in the production handoff with Clinical Applications across RIS, PACS, reporting, and related clinical technology systems.

• Evaluate infrastructure, edge server, network, compute, storage, security, encryption, access controls, and HIPAA compliance requirements.

• Assess vendor technical maturity, scalability, supportability, regulatory status, performance claims, and integration complexity.

• Provide technical insights for vendor contract negotiations, including SLAs, model retraining frequency, and performance guarantees.

• Remain updated on clinical imaging AI vendors, modalities, FDA clearances, and CPT reimbursement codes.

• Identify opportunities to enhance Lumexa's clinical AI portfolio and contribute to AI governance and validation thought leadership.

⛳️ Requirements

• Over 5 years of experience in clinical imaging informatics, radiology AI deployment, or imaging AI vendor field engineering.

• Practical experience installing and configuring clinical AI software across sandbox, edge server, on-prem, or cloud environments, including data routing, anonymization, and system configuration.

• Familiarity with clinical imaging workflows, including the procedures radiologists use to read studies, interpret findings, and finalize reports.

• Proficiency in DICOM, HL7, FHIR, and PACS/RIS architecture.

• Hands-on Python or equivalent scripting skills for validation pipelines, data extraction, and comparison analysis.

• Experience with LLM/NLP techniques for text comparison, semantic similarity, or structured information extraction from clinical reports.

• Background in designing and executing AI performance validation studies, including metrics, ground truth, and study methodology.

• Experience in building or enhancing automated de-identification and data preparation pipelines, including PACS cohort selection, DICOM header and burned-in pixel anonymization, paired report de-identification, and secure vendor packaging.

• Practical experience with DICOM routing and anonymization platforms such as Laurel Bridge Compass or RSNA CTP, as well as complementary tools like Presidio, AWS Comprehend Medical, or OCR-based pixel masking is highly desired.

• Capability to collaborate effectively with clinical leadership and technical IT stakeholders.

• Ability to work independently in ambiguous, fast-paced environments with minimal oversight.

• Strong skills in project scoping, prioritization, and execution across multiple concurrent evaluations and projects.

• Preferred: clinical knowledge of CT, MRI, mammography, X-ray, and ultrasound workflows.

• Preferred: experience with clinical imaging AI vendor solutions, field, or implementation engineering.

• Preferred: CIIP certification or equivalent.

• Preferred: experience as a radiology technologist, imaging informaticist, or radiology research engineer.

• Preferred: familiarity with AWS, Azure, or GCP.

• Preferred: knowledge of FDA 510(k) clearance and CPT reimbursement codes.

• Preferred: understanding of HIPAA and healthcare compliance.

• Preferred: advanced degree in biomedical engineering, medical imaging, computer science, or a related field.

🏝️ Benefits

• Opportunity to work with cutting-edge clinical AI technologies.

• Collaborative work environment with clinical and technical experts.

• Professional development and growth opportunities within the organization.