Associate Sales Engineer
Rad AIUnited StatesPosted 10 June 2025
Job Description
Associate Sales Engineer
ABOUT RAD AI
At Rad AI, we’re on a mission to transform healthcare with artificial intelligence. Founded by a radiologist, our AI-driven solutions are revolutionizing radiology—saving time, reducing burnout, and improving patient care. With one of the largest proprietary radiology report datasets in the world, our AI has helped uncover hundreds of new cancer diagnoses and reduced error rates in tens of millions of radiology reports by nearly 50%.
Rad AI has secured over $140M in funding, including a recently oversubscribed Series C ($68M round) led by Transformation Capital, bringing our valuation to $528M. Our investors include Khosla Ventures, World Innovation Lab, Gradient Ventures, Cone Health Ventures, and others—all backing our mission to empower physicians with cutting-edge AI.
Our latest advancements in generative AI are used by thousands of radiologists daily, supporting more than one-third of radiology groups and healthcare systems and nearly 50% of all medical imaging in the U.S. at partners including Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health.
Recognized as one of the most promising healthcare AI companies by CB Insights and AuntMinnie https://www.radai.com/news/auntminnie-recognizes-rad-ai-omni-reporting-as-2023s-best-new-radiology-software, and ranked by Deloitte https://www2.deloitte.com/us/en/pages/technology-media-and-telecommunications/articles/fast500-winners.html as the 19th fastest-growing company in North America, we are building AI-powered solutions that make a real impact. Most recently, Rad AI was named to CNBC’s Disruptor 50 https://www.cnbc.com/2025/06/10/2025-cnbc-disruptor-50-see-the-full-list-of-companies.html list, highlighting the innovation and momentum behind our mission.
If you’re ready to shape the future of healthcare, we’d love to have you on our team!
HERE’S WHAT YOU’LL BE DOING
You’ll be the technical backbone of our pre‑sales motion, making it simple for radiology groups and health systems to understand how Rad AI fits into their infrastructure, security posture, and clinical workflows. You’ll own the first pass on technical questionnaires and RFPs, orchestrate input from Security, Product, and Engineering, and build the reusable content that makes every next deal easier than the last.
Day to day, you’ll partner closely with Sales Executives to guide opportunities from early discovery through technical validation. You’ll surface workflow constraints and integration requirements early, document assumptions clearly, and help set up deployments for success before contracts are even signed. Along the way, you’ll keep learning—about PACS, RIS, EHRs, AI in imaging, and the realities of enterprise healthcare IT—and you’ll feed that learning back into how we sell.
In addition, you will:
- Own the first pass on technical and security questionnaires, using internal tools and playbooks and pulling in the right experts at the right time.
- Draft technical sections of RFIs and RFPs, maintaining and improving a central repository of standard answers, security positions, and AI governance language.
- Anticipate and address common technical objections—around HIPAA, SOC 2, data flows, and integrations—so customers feel confident moving forward.
- Support discovery and demo prep by documenting workflow requirements, architecture diagrams, and implementation assumptions for each strategic opportunity.
- Help design and refine demo environments, scripts, and technical enablement materials that make our products and integrations feel tangible for radiologists and IT.
YOU NEED THESE QUALIFICATIONS
- You have 3+ years of experience in a sales engineering, technical pre‑sales, or technical support role working with enterprise software.
- You have hands-on experience supporting healthcare IT or other highly regulated enterprise environments (e.g., health systems, radiology groups, or clinical SaaS).
- You commun ... (truncated, view full listing at source)
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