Rad AI

• Own demand generation strategy and performance: Lead and shape Rad AI’s full-funnel demand generation plan, connecting business priorities, budget and pipeline goals. • Lead integrated campaigns: Develop and execute programs across paid social, search, retargeting, email, webinars, partner channels and targeted account-based programs. • Partner with Marketing Operations: Define campaign requirements, audience logic, scoring, routing, attribution and reporting needs. Maintain enough HubSpot fluency to validate setup and troubleshoot issues. • Manage budget and channel performance: Allocate investment, manage agencies and make clear decisions about where to scale, adjust or stop spending. • Analyze and optimize: Track funnel performance, test messaging and channels and turn data into actions that improve conversion and pipeline. • Drive cross-functional execution: Align with Sales, RevOps, Product Marketing and Marketing Communications on priorities, handoffs and follow-up. • Create operating discipline: Build clear plans, owners, milestones and deadlines. Communicate risks early, close loops and ensure campaigns move from strategy to launch.

• Design and implement the data architecture, ensuring scalability, flexibility, and efficiency using pipeline authoring tools like Metaflow and large-scale data processing technologies like Spark. • Define and extend our internal standards for style, maintenance, and best practices for a high-scale data platform. • Collaborate with researchers and other stakeholders to understand their data needs including model training and production monitoring systems and develop solutions that meet those requirements. • Take ownership of key data engineering projects and work independently to design, develop, and maintain high-quality data solutions. • Ensure data quality, integrity, and security by implementing robust data validation, monitoring, and access controls. • Evaluate and recommend data technologies and tools to improve the efficiency and effectiveness of the data engineering process. • Continuously monitor, maintain, and improve the performance and stability of the data infrastructure.

• Manage and qualify inbound leads from marketing campaigns, website forms, events, and partner channels • Conduct personalized outbound outreach (email, LinkedIn, phone) to targeted accounts to generate new pipeline • Research target accounts — radiology practices, health systems, and academic centers — to map org structure and identify the right stakeholders • Tailor outreach based on persona (clinical, economic, strategic, technical), segment, and likely use case • Master the Rad AI story and clearly articulate our value to radiologists, IT leaders, and executive buyers • Partner closely with Account Executives to build qualified pipeline and hand off meetings that align to agreed-upon SLAs • Document all activity, notes, and lead status accurately and consistently in HubSpot • Execute and refine sequenced cadences across key segments (private practice, community systems, academic centers, IDNs) • Share feedback on messaging, ICP fit, objections, and lead quality to continuously improve Marketing and Sales alignment • Meet and exceed core MDR metrics: activities, meetings set, show rates, and qualified pipeline created

• Lead product training and support go-live: Play an integral role in implementation projects by leading product-related training and supporting go-live stabilization through engagement with customer admins and radiologists. • Develop product expertise: Develop deep functional knowledge of one Rad AI product, articulating key features, workflows, and integrations. • Understand core product workflows: Develop a deep understanding of core product workflows and best practices recommendations. • Stay current on features and integrations: Stay current on new features, tools, and available integrations, and share that knowledge with pertinent Implementation team members. • Create training materials: Assist in building training materials as needed. • Facilitate team communication: Facilitate basic communication between implementation and product/engineering/technical support teams. • Manage vendor tasks and escalations: Assist in tracking third-party vendor-related tasks and communications, escalating issues as needed, and documenting vendor interactions. • Address product queries: Respond to product-related queries from customers and internal stakeholders as needed. • Drive project success: Support project success through diligent execution of product-related training, learning internal processes, and communicating effectively within the immediate team. • Act as a radiology workflow consultant: Serve as a trusted advisor to clinical and operational stakeholders, translating customer-specific radiology workflows into optimized product configurations and adoption strategies — not just training delivery. • Conduct workflow discovery and gap analysis: Lead structured pre- and post-go-live workflow assessments with radiologists, department leads, and IT stakeholders to identify friction points, configuration needs, and adoption risks. • Support pre-sales engagements: Partner with Sales to provide product and workflow expertise during demos and scoping discussions, helping translate prospect needs into implementation requirements. • Communicate effectively: Demonstrate strong verbal and written communication skills.

• Work independently to plan, monitor, and manage multiple complex customer-facing projects • Lead the end-to-end delivery of Rad AI’s products to radiology practices and health systems, from kick-off to go-live and transition to support • Facilitate Discovery sessions to understand client workflows, requirements, and success criteria • Develop detailed project plans, including timelines, milestones, and resource needs • Coordinate cross-functional teams, including Product, Engineering, and Integration resources, to meet project objectives and deadlines • Serve as the primary client-facing contact throughout the implementation • Ensure a smooth onboarding process by managing project timelines, dependencies, and communications with executive, clinical, and IT stakeholders • Track and manage feature requests, ensuring clear communication, documentation, and prioritization • Monitor project health, proactively identify risks, and escalate blockers, as needed • Issue resolution and mitigation strategies based on data-driven decision making • Conduct weekly status meetings with internal and external stakeholders • Collaborate and coordinate with Rad AI’s product, engineering, and customer success teams for project goal setting, data integration, testing, and product feedback • Provide ongoing updates to leadership throughout the project, via dashboards and reports • Partner with cross-functional teams, including Support and Client Success, to ensure customers are prepared for go-live and long-term success • Suggest process improvements and help with maintaining onboarding templates, documentation, and best practices • Contribute to building a world-class implementation organization that aims to exceed customer expectations with attentive, responsive, and knowledgeable service

Role Description We are looking for a senior leader to take our Orchestration platform from concept to a credible, market-ready product and business. You will operate as the product and business owner of Orchestration within Rad AI. - Own Orchestration end-to-end – lead strategy from concept through launch and commercialization, and be accountable for adoption, revenue, and platform impact. - Define the platform narrative – articulate how Orchestration fits into the broader Rad AI platform and the market story we tell customers, partners, and investors. - Translate market needs into execution – turn customer and ecosystem signals into clear product priorities, execution plans, and launch milestones. - Drive cross-functional alignment – connect product, engineering, sales, partnerships, implementations, and leadership into a single, coherent motion. - Build the commercial strategy alongside the product strategy – pricing and packaging, partner model, design partnerships, market positioning, and rollout plan. - Make the build / partner / buy calls – evaluate options across orchestration-related capabilities and decide where we build, where we partner, and where we acquire. - Hit high-stakes timelines – own delivery against major industry moments and launch deadlines, and be the central point of accountability for unblocking teams. - Prioritize the highest-value bets – identify the most important opportunities across workflow, interoperability, routing, and adjacent platform capabilities, and say no to the rest. - Operate like a founder – step into whatever role the moment calls for—contracts, partner negotiations, customer escalations, technical tradeoffs—while keeping your eyes on the long-term build. Qualifications - You have a commercial mindset: you think beyond feature delivery and understand how products create revenue, strategic leverage, and long-term platform value. - You have deep industry experience in radiology, imaging, PACS, workflow, interoperability, DICOM, routing, or adjacent enterprise imaging infrastructure. - You have led major product or platform initiatives before, likely as a Head of Product, GM, or senior product leader in a relevant healthcare or imaging company. - You can operate with autonomy, influence executives, and make decisions in ambiguity. - You have a track record of turning ambiguous strategic ideas into shipped products and real customer adoption. Requirements - It would be nice if you have launched a platform or interoperability product into a regulated, enterprise environment. - You are familiar with the ecosystem of imaging vendors, workflow vendors, AI partners, and health system stakeholders. - You have shaped pricing, packaging, and partner models for a platform product. - You have worked with AI/ML products in mission-critical environments. - You are energized by a remote-first, highly cross-functional environment. Benefits - Comprehensive Medical, Dental, Vision & Life insurance - HSA (with employer match), FSA, & DCFSA - 401(k) - 11 Paid Company Holidays - Flexible PTO policy - Annual company-wide offsite - Periodic team offsites - Annual equipment stipend

Role Description As a Radiology Transcriptionist, you will be responsible for proofreading and helping to correct radiology report language generated using speech AI models, error correction models, and other generative AI tools. You'll work closely with our Transcription Manager and ML Research team to ensure report language is accurate, complete, and adheres to national clinical and Rad AI guidelines. What You'll Be Doing - Proofread and help correct radiology report language generated from radiologist dictation and generative AI tools. - Verify medical terminology, anatomical terms, and report formatting for accuracy and consistency. - Maintain strict adherence to patient confidentiality and HIPAA regulations. - Provide feedback on common errors or inconsistencies and audio quality in dictated or generated content to help improve future speech models. Qualifications - 3+ years of experience as a medical transcriptionist. - Strong knowledge of medical terminology, particularly related to imaging and diagnostics. - Excellent attention to detail and individual grammatical variability. - Familiarity with speech recognition and transcription software. - Ability to work independently and manage tight turnaround times. Nice To Haves - Experience working with speech to text AI tools. - Certification in medical transcription / healthcare documentation (CHDP / CHDS / RHDS) and/or radiology-specific transcription training. Benefits - Comprehensive Medical, Dental, Vision & Life insurance - HSA (with employer match), FSA, & DCFSA - 401(k) - 11 Paid Company Holidays - Flexible PTO policy - Annual company-wide offsite - Periodic team offsites - Annual equipment stipend

Role Description We’re looking for a Senior Implementation Engineer with extensive experience with interfaces to clinical data systems. Rad AI’s award-winning software has experienced tremendous market growth. We are looking for a teammate with a “can do” attitude that is adaptable in a fast-paced, high-growth team. - Develop and maintain HL7 and FHIR interfaces with our customers' systems, working closely with the customer's interface teams. - Lead the standardization of our interfaces across products and the creation of documentation for our interfaces. - Provide technical expertise, guidance, and support during product implementation to ensure successful customer utilization. - Work on monitoring and alerting of interface health. - Test and troubleshoot HL7 and FHIR implementations to ensure reliability and compatibility. - Facilitate end-to-end implementation testing with customers. - Provide end-to-end technical assistance for our new clients during their implementation testing process. - Collaborate with Developers and Engineers on interface-related tasks to continually improve integration methods and/or custom functionality to meet customer needs. - Provide advanced technical customer support as necessary after go-live. - Assist in mentoring and upskilling teammates in HL7 and FHIR, and acting as an internal leader in FHIR and HL7 best practices. Qualifications - 5+ years of experience in HL7 v2 interfacing. - Proven technical background, should be comfortable reading logs, source code, querying DBs using SQL. - Familiarity with REST APIs, JSON, and XML. - Familiarity/Experience with JavaScript, Typescript, and/or Python. - Strong understanding of the Healthcare IT ecosystem and major clinical and system integration points. - A desire to become an expert with FHIR. - Strong attention to detail, and experience in testing and validating data mappings. - Ability to communicate effectively with customer IT and end users, as well as our product management and engineering. - Willingness to learn and adapt in a fast-paced startup environment. Requirements - Strong understanding of radiology workflow. - Experience with FHIR. - Experience in a healthcare startup. Benefits - Comprehensive Medical, Dental, Vision & Life insurance - HSA (with employer match), FSA, & DCFSA - 401(k) - 11 Paid Company Holidays - Flexible PTO policy - Annual company-wide offsite - Periodic team offsites - Annual equipment stipend

• Architect and evolve our cloud infrastructure (primarily on AWS) across container orchestration (Kubernetes, Elastic Container Service), serverless (e.g., Lambda), virtual machines (e.g., EC2), and data stores to support current and future products. • Collaborate with engineering leadership, machine learning, data science, and product partners to help shape our platform vision. • Develop and maintain tooling that improves engineering productivity and developer experience. • Promote sustainable incident response and lead blameless post-incident reviews. • Manage network and systems monitoring, design alert strategies, and participate in an equitable on‑call rotation.

• Own core planning processes that guide company decision-making. • Manage and continuously improve the company’s monthly forecasting process • Maintain and evolve the company’s operating model across revenue, expenses, and cash • Develop scenario models to support planning, investment decisions, and board discussions • Leverage cutting-edge AI tools to scale our financial operations • Provide leadership with clear insights into company performance and key drivers. • Lead financial budget vs. actual performance reviews with executive team members • Translate financial results into actionable insights for the executive leadership team • Develop executive-ready reporting and dashboards that track the company’s most important KPIs • Support leadership in evaluating the company’s most important strategic decisions. • Partner with the executive team to evaluate new products, partnerships, and growth initiatives • Support leadership in prioritizing investments across product development, infrastructure, and go-to-market • Help the company understand and optimize the economics of AI infrastructure. • Partner with engineering and product leadership to analyze AI infrastructure costs and scaling dynamics • Build frameworks to evaluate unit economics across AI compute, model inference, and platform usage