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 or APIs

• 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