Data Engineer
Senior Data Engineer building scalable data pipelines and infrastructure on AWS using Spark, Metaflow, and container orchestration. Requires 5+ years of experience designing distributed data systems.
Generative AI platform for radiology reporting
Rad AI builds AI software like Reporting, Impressions, and Continuity to automate radiology workflows, generate impressions, and manage patient follow-ups. It serves radiologists and health systems to save time, reduce burnout, and improve accuracy and patient care. The platform handles nearly half of US medical imaging, enhancing efficiency amid rising volumes and shortages.
Senior Data Engineer building scalable data pipelines and infrastructure on AWS using Spark, Metaflow, and container orchestration. Requires 5+ years of experience designing distributed data systems.
Market Development Representative generating qualified pipeline for Sales through inbound lead qualification and outbound prospecting to radiology groups and health systems. Requires 2+ years sales experience and healthcare/radiology background.
Full-cycle Recruiter to source, screen, and hire across engineering, product, customer success, and operations at a fast-growing healthcare AI startup. Requires 4+ years of tech startup recruiting experience and Ashby ATS proficiency.
Own roadmap and delivery for Rad AI's orchestration platform, turning product direction into shipped workflow capabilities that integrate with radiology IT systems. Requires workflow-heavy enterprise PM experience, technical fluency, and healthcare imaging domain knowledge.
Own the roadmap and execution for Rad AI's SDK and DICOM routing capabilities. Define developer experience, APIs, and integration patterns that enable ecosystem partners to build on the platform.
Own the vision, roadmap, and commercial strategy for Rad AI's Orchestration platform. Lead cross-functional execution from concept to market-ready product, driving adoption and revenue in radiology workflow and interoperability.
Develop and maintain HL7 and FHIR interfaces with clinical systems, leading standardization, testing, and customer implementations for a healthcare AI platform. Requires 5+ years HL7 experience, SQL, APIs, and healthcare IT knowledge.
Leads core product engineering team owning roadmap execution, architecture decisions, and cross-functional partnerships to deliver reliable AI systems for healthcare. Requires 6+ years managing engineers with hands-on experience in modern web/cloud stacks.
Leads Rad AI's Continuity product as GM, owning strategy, roadmap, cross-functional team, and growth in healthcare AI for radiology follow-up. Requires experience scaling SaaS businesses, leading engineering/product teams, and navigating clinical realities.
Leads end-to-end software implementation projects for healthcare customers, managing timelines, cross-functional teams, and stakeholder communications to ensure successful deployments of AI radiology platform. Requires 2+ years project management experience, preferably in healthcare IT with familiarity in HL7, FHIR, and EHRs.
Leads engineering team building Rad AI's flagship Reporting product, owning technical strategy, architecture for data-intensive radiology reporting software, and scaling high-performing teams in a healthcare AI environment. Requires 10+ years engineering and 5+ years managing managers.
Designs and operates scalable AWS-based cloud infrastructure including Kubernetes, serverless, and data stores. Collaborates on platform vision, builds productivity tools, manages monitoring/on-call, and requires 6+ years in cloud-native environments with IaC expertise.
Designs, builds, and operates scalable cloud infrastructure on AWS with Kubernetes and serverless tech to support AI healthcare products. Requires 4+ years experience in cloud-native platforms, IaC, automation, and reliability practices for regulated environments.
Designs and operates scalable cloud infrastructure on AWS, focusing on Kubernetes orchestration, reliability practices, and observability for AI healthcare products. Requires 8+ years experience with IaC, containerization, and cross-team leadership.
Leads end-to-end applied ML research in NLP, LLMs, retrieval, and multimodal models for healthcare AI, driving from experimentation to production deployment with rigorous evaluation and clinician collaboration. Requires 7+ years experience, MS/PhD, and depth in ML areas like PyTorch tooling.