Senior Engineering Manager

Rad AI•San Francisco, CA

About The Position

Rad AI is a rapidly growing healthcare AI company on a mission to transform healthcare with artificial intelligence. Founded by a radiologist, our AI-driven solutions are revolutionizing radiology by saving time, reducing burnout, and improving patient care. We have secured significant funding and our AI is used by thousands of radiologists daily, supporting a substantial portion of medical imaging in the U.S. We are recognized as a promising healthcare AI company and are building AI-powered solutions that make a real impact. We are looking for individuals passionate about driving innovation and delivering impactful healthcare solutions to join our mission-driven team.

Requirements

6–8+ years of experience managing software engineers with a proven track record leading teams that ship and operate production software at scale.
A strong engineering foundation where you started as a hands-on engineer and are still comfortable going deep in technical discussions even if you’re no longer the primary coder.
Experience leading teams building production web or cloud applications in modern stacks (e.g., Python, TypeScript/JavaScript, React, distributed systems on a major cloud provider).
Excellent execution and stakeholder management: you set clear priorities, navigate tradeoffs, and keep teams aligned when requirements evolve.
Strong communication across technical and non-technical audiences with a track record of influencing across functions without formal authority.
A pragmatic, outcomes-oriented mindset where you’ve balanced ideal architecture with real-world constraints and have bias toward incremental, value-driven delivery.
Genuine enjoyment of building and scaling healthy engineering teams: hiring, onboarding, performance management, and career development.

Nice To Haves

You’ve worked in healthtech, healthcare data, or a regulated environment (HIPAA, PHI, SOC 2) and understand what that demands from a software team.
You’re familiar with radiology workflows or adjacent clinical systems (PACS, RIS, EHR, HL7/FHIR, DICOM).
You’ve led teams that work closely with ML/AI systems in production and understand what’s different about those operational challenges.
You’ve managed multiple teams or a small org, including partnering with Staff or Principal engineers to set technical direction.

Responsibilities

Own end-to-end execution on your team’s roadmap from planning, prioritization, delivery, rollout, and iteration across one or more core products.
Raise the technical bar by guiding architecture and design decisions, ensuring your team builds observable, maintainable systems that meet healthcare-grade reliability standards.
Partner cross-functionally with Product, Implementations, Design, Clinical, Customer Success, and GTM counterparts to translate customer problems into clear, actionable engineering work.
Drive continuous improvement across planning, estimation, code review, incident response, on-call, and documentation while evolving team processes and pushing the limits of AI to unlock new levels of efficiency and quality.
Use data and metrics to drive decisions, defining and tracking the right leading indicators for reliability, performance, and delivery health.
Hire exceptional engineers, develop the talent already on your team, and foster a culture of psychological safety, ownership, and continuous learning.