Software Engineer, Voice AI

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.

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.

• 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

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

• 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

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.