Software Engineer, Voice AI
About Sage Care
Sage Care is a fast-growing, early-stage healthcare startup founded by exceptional leaders from Apple, Uber, Carbon Health and backed by top-tier venture capital (General Catalyst, Chelsea Clinton). With a strong customer pipeline, Sage Care is transforming healthcare by simplifying care navigation.
Our platform makes it easier for patients to find the right doctor, helps providers focus on those who need them most, and ensures faster access to care, delivering better care and stronger economic outcomes at scale through harnessing the latest AI innovations.
Building on our successful collaborations with health systems across the U.S., we have expanded internationally to the MENA region. We are now partnering with health systems there to deploy our AI-powered care navigation platform.
About the Role
Our AI voice agents talk to real patients every day. This role is where those conversations get better.
We are hiring a product-minded Software Engineer to help build and improve Sage Care's voice AI platform. You will ship features to production, debug issues from live calls, and improve how our agents perform in practice. This is a hands-on role where you will learn how AI systems behave in the real world and what it takes to make them reliable, fast, and genuinely helpful to the person on the phone.
You will work closely with experienced engineers and product to deliver high-quality voice experiences for patients and providers, with real ownership from your first weeks.
What You'll Do
Build and ship features for AI-powered voice experiences
Debug issues from real calls and improve system behavior
Work with the components of a production voice stack: transcription, LLMs, and APIs
Help improve latency, reliability, and conversation quality
Contribute to testing, monitoring, and observability
Collaborate closely with product to iterate on user experience
What We're Looking For
Required
2 to 3 years of software engineering experience
Strong programming skills (Python preferred)
Experience building backend systems, APIs, or services that handle real user requests
Product mindset: cares about user experience and outcomes
Eagerness to learn and work in a fast-paced environment
Comfortable with ambiguity and problem-solving
Nice to Have
Exposure to AI/ML or LLM-based applications
Experience with real-time systems or APIs
Interest in voice systems or conversational AI
Experience at a startup or small team
What Success Looks Like
Ships features that improve real patient and provider experience
Can debug and fix issues in production with guidance
Gains a working understanding of how AI systems behave in practice
Contributes to improving system reliability and performance
Grows into owning components end-to-end
Why This Role Matters
Most engineers wait years to work on systems that matter this directly. Here, the code you ship changes whether a patient reaches care today. You will learn production AI from engineers who operate it every day, on a system where quality is not abstract: it is a phone call with a person who needs help.