Product AI Engineer, Voice Systems
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
We’re hiring a product-minded AI Engineer to help build and improve Sage Care’s AI Voice platform.
You’ll work on real customer-facing systems: helping ship features, debug issues from live calls, and improve how our voice agents perform in practice. This is a hands-on role where you’ll learn how AI systems behave in the real world and how to make them reliable, fast, and user-friendly.
You’ll work closely with experienced engineers and product to deliver high-quality voice experiences for patients and providers.
Key Responsibilities
Build and ship features for AI-powered voice experiences
Debug issues from real calls and improve system behavior
Work with components like 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
Qualifications
Required
2–3 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 in This Role
Ships features that improve real customer experience
Can debug and fix issues in production with guidance
Gains understanding of how AI systems behave in practice
Contributes to improving system reliability and performance
Grows into owning components end-to-end
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