Staff Software Engineer, Speech

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, and ranked by Deloitte 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 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!

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  Act as technical lead for the Speech function: set direction, drive architecture decisions, and mentor engineers

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  Partner with Research Scientists to take speech models from evaluation to production

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  Build and evolve real-time audio capture and streaming in our React/TypeScript web application

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  Design and operate the distributed Python backend services that power our speech platform

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  Contribute to the infrastructure behind our speech systems

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  Debug and improve production reliability and performance using modern observability tools

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  Work with Product, UX, and Customer Success to ship features in a high-scale, HIPAA-compliant environment

• 7+ years of industry experience developing audio or multimedia software

• Strong full-stack skills: in-depth TypeScript/React and Python

• Experience with browser audio APIs (Web Audio, AudioWorklet) and real-time audio streaming

• Strong experience with WebSockets and real-time client–server communication

• Experience building and operating distributed systems

• Comfortable debugging production issues with observability tools (e.g. Sentry, Grafana)

• Proven technical leadership: mentoring engineers and driving technical direction across a team

• Strong testing practices (unit and integration) and experience on distributed teams

• Experience with FastAPI, SQLAlchemy, and PostgreSQL

• Experience with Infrastructure as code, particularly Terraform

• Experience with ASR/STT, or ML-driven products such as speech recognition or NLP, from model evaluation (e.g. word error rate) through rollout and production monitoring

• Experience with spec-driven development and AI-assisted engineering tools (e.g. Claude Code)

• Experience in HIPAA-compliant environments, especially FHIR and HL7

• Experience working at startups

• Experience with 3rd-party integrations such as Auth0

• Experience with relational and document based databases, as well as other large scale data storage paradigms

Join our world-class team as we build and deploy AI solutions that empower physicians and transform patient care—making a meaningful impact on millions of lives. Driven by our mission,  we prioritize transparency, inclusion, and close collaboration, bringing together exceptional people to revolutionize healthcare. If you're passionate about driving innovation and delivering impactful healthcare solutions, we'd love to hear from you!

To learn more about what it's like to work at Rad AI, visit https://www.radai.com/life-at-rad-ai and be sure to follow us on LinkedIn to stay up to date!

For roles listed as San Francisco - Onsite:

• This role will be based in our San Francisco office and we expect employees to work onsite four days per week. The remaining time may be worked remotely or onsite, depending on team and business needs.

For roles listed as United States - Remote:

• This role is open to candidates located anywhere in the United States.

For roles listed as San Francisco - Onsite + United States - Remote:

• We will prioritize candidates who can work onsite four days per week in San Francisco, while also considering remote candidates located anywhere in the United States.