Staff AI Engineer, Voice Agents
About The Position
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 Staff AI Engineer to lead the design and evolution of Sage Care’s AI agents, with a focus on voice systems. This role focuses on building and operating AI agents that perform reliably in real-world conditions. You’ll own how our agents behave end-to-end — from orchestration and tool use to latency, evaluation, and failure handling. You’ll work on complex, non-deterministic systems and design the architecture needed to make them consistent, observable, and scalable in production.
Requirements
- 7+ years of software engineering experience
- Experience building and operating AI agents or conversational systems in production
- Strong understanding of:
- agent orchestration and tool use
- multi-step workflows and control flow
- LLM behavior in real-world settings
- Experience designing evaluation systems for AI quality
- Strong debugging skills across complex, non-deterministic systems
Nice To Haves
- Experience with voice systems (speech-to-text, text-to-speech, real-time pipelines)
- Experience building customer support agents or similar systems
- Experience optimizing low-latency / real-time AI systems
- Experience working with multiple model providers or inference stacks
Responsibilities
- Design and own AI agent architecture (orchestration, tool use, control flow)
- Build systems that enable agents to operate reliably across real-world interactions
- Develop and improve evaluation frameworks for agent quality and behavior
- Debug and resolve complex issues in production (edge cases, failures, regressions)
- Optimize performance across the stack (latency, cost, reliability)
- Define patterns and best practices for building and operating AI agents
- Mentor engineers and raise the bar on AI systems design and execution
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
