Application Implementation Engineer – AI Implementation

Job not on LinkedIn

🔥 9 minutes ago

🌲 North Carolina – Remote

🌲 North Carolina – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Lumexa Imaging

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2018

🏥 Healthcare

🤝 B2B

Healthcare • B2B

Lumexa Imaging is a national outpatient diagnostic imaging company building partnerships with health systems to expand access to advanced medical imaging. It operates 185+ outpatient imaging centers across 13 states (including 85+ centers run as joint ventures with health systems), provides centralized scheduling, subspecialized radiologist interpretations (including teleradiology through its Connexia offering), and leverages AI and state-of-the-art equipment to improve clinical quality and operational efficiency. Lumexa focuses on patient experience, convenient outpatient care that can be lower-cost than hospital outpatient departments, and collaborative joint ventures with health systems.

📋 Description

• Lead technical evaluation, validation, implementation, integration, and clinical adoption of third-party clinical AI solutions • Install, configure, and maintain clinical AI software across sandbox, edge server, on-premise, and cloud environments • Establish DICOM routing, HL7 messaging, and de-identification workflows for images and reports • Design and execute structured AI validation studies using appropriate metrics such as sensitivity, specificity, discrepancy rates, and clinical/workflow impact • Build LLM/NLP-based frameworks to compare AI outputs with radiologist ground truth • Develop Lumexa's reusable clinical AI validation playbook and automated evaluation tooling • Author evidence-based go/no-go recommendations for the AI Governance Council, including risk assessment and deployment scope • Partner with clinical leadership to define ground truth, acceptance thresholds, workflow fit, and clinical priorities • Translate validated AI capabilities into deployment-ready integration designs for radiologist workflows • Map current- and future-state workflows and identify workflow risks, change-management considerations, and adoption barriers • Support production handoff with Clinical Applications across RIS, PACS, reporting, and related clinical technology systems • Assess infrastructure, edge server, network, compute, storage, security, encryption, access controls, and HIPAA compliance requirements • Evaluate vendor technical maturity, scalability, supportability, regulatory status, performance claims, and integration complexity • Provide technical input for vendor contract negotiations, including SLAs, model retraining cadence, and performance guarantees • Stay current on clinical imaging AI vendors, modalities, FDA clearances, and CPT reimbursement codes • Identify opportunities to expand Lumexa's clinical AI portfolio and contribute to AI governance and validation thought leadership

🎯 Requirements

• 5+ years of experience in clinical imaging informatics, radiology AI deployment, or imaging AI vendor field engineering • Hands-on experience installing and configuring clinical AI software across sandbox, edge server, on-prem, or cloud environments, including data routing, anonymization, and system configuration • Working knowledge of clinical imaging workflows, including how radiologists read studies, interpret findings, and finalize reports • Fluency with 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 • Experience designing and executing AI performance validation studies, including metrics, ground truth, and study methodology • Experience building or improving 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 • Hands-on experience with DICOM routing and anonymization platforms such as Laurel Bridge Compass or RSNA CTP, alongside complementary tooling such as Presidio, AWS Comprehend Medical, or OCR-based pixel masking, strongly desired • Ability to collaborate with clinical leadership and technical IT stakeholders • Ability to operate independently in ambiguous, fast-moving environments with minimal oversight • Strong project scoping, prioritization, and execution skills across multiple concurrent evaluations and projects • Preferred: clinical knowledge of CT, MRI, mammography, X-ray, and ultrasound workflows • Preferred: clinical imaging AI vendor solutions, field, or implementation engineering experience • Preferred: CIIP certification or equivalent • Preferred: experience as a radiology technologist, imaging informaticist, or radiology research engineer • Preferred: experience with AWS, Azure, or GCP • Preferred: familiarity with FDA 510(k) clearance and CPT reimbursement codes • Preferred: HIPAA and healthcare compliance knowledge • Preferred: advanced degree in biomedical engineering, medical imaging, computer science, or related field