Rad AI

Product Manager, SDK

San Francisco · Full-time

Sponsorship not specifiedDetected 61 days ago

RESTLLMsAI OrchestrationValuationPatient CareRadiologyLeadershipCollaboration

About the role

This is a high-priority role with tight timelines.
We need a Product Manager who can move quickly, work cross-functionally, and connect technical execution with a broader commercial and platform strategy.
Start from what we already have-work with engineering and technical stakeholders to evaluate existing infrastructure and integration patterns instead of reinventing from scratch.

Own the roadmap and execution for the Rad AI SDK and DICOM routing product initiatives, end-to-end.
Define the developer experience for partners building on Rad AI-APIs, SDK surfaces, documentation, onboarding flows, and the integration patterns that make adoption straightforward.
Lead partner integrations across the ecosystem (AI vendors, modality/PACS providers, reporting tools, downstream care systems), making sure partners can ship integrations quickly and reliably.
Drive clear scope, sequencing, owners, and milestones toward a credible RSNA story and launch plan.
Partner with leadership to ensure product decisions support the broader platform and commercialization narrative.
routing standardizes how images and AI outputs move, and the SDK standardizes how partners build on top of it.
Drive requirements and delivery for image routing, orchestration workflows, and the routing primitives exposed through the SDK.
You will own product planning and execution for the Rad AI SDK and the DICOM routing capabilities it exposes to partners.
You'll define the developer experience, the integration patterns, and the routing workflows that let ecosystem partners build on Rad AI's platform.
Have run partner or ecosystem programs where external teams build on top of your product.

You are a product manager with experience shipping SDK, API, or developer-platform products-someone who has set external builders up for success and is comfortable owning a developer experience end-to-end.
You have experience with DICOM, imaging workflows, radiology IT, PACS, routing, or interoperability products (strongly preferred).
You've shipped technical platform or infrastructure-adjacent products and are comfortable in dependency-heavy systems and detailed implementation conversations.
You can translate strategic direction into concrete product plans and execution, with clear scope, owners, and milestones.
You have strong technical fluency and can operate in dependency-heavy systems, partnering closely with engineers on tradeoffs and integration details.
Have worked on imaging infrastructure, routing, interoperability, or workflow systems.
Can keep multiple technical threads moving at once.
Are pragmatic about sequencing and dependencies.

which studies get routed where, how outputs come back, and how everything stays in sync with the radiologist's workflow.
DICOM routing is the plumbing that makes the rest of the platform possible.
Together, DICOM routing and the

At Rad AI, we're on a mission to transform healthcare with artificial intelligence.
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.
If you're ready to shape the future of healthcare, we'd love to have you on our team!
Comprehensive Medical, Dental, Vision & Life insurance
HSA (with employer match), FSA, & DCFSA
Flexible PTO policy
Annual equipment stipend

Bring partner-generated content-preliminary reports, findings, measurements, and other outputs-into the product in a way that is easy for customers to evaluate and adopt.
Founded by a radiologist, our AI-driven solutions are revolutionizing radiology-saving time, reducing burnout, and improving patient care.
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.

This listing is sourced directly from Rad AI's careers page and normalized into a canonical job model.