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.
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.
This is a hands-on role. You will write code, debug production issues, and directly improve systems.
We are looking for engineers who have personally built and operated production AI systems or real-time systems.
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
7+ years of software engineering experience
Experience building and operating user-facing , real-time production systems
Experience building production AI systems (agents, conversational systems, or ML-powered workflows) that handle real user interactions end-to-end
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
Experience working with systems where latency, correctness, and reliability matter simultaneously (e.g. real-time decisioning, interactive systems, or high-throughput services)
Demonstrated experience owning systems in production: including oncall, debugging incidents, and improving systems based on real usage
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
Agents that handle real-world interactions reliably and predictably
Clear, scalable agent architecture (not ad-hoc or fragile systems)
Strong evaluation loops that continuously improve agent quality
Fast identification and resolution of production issues
Systems that balance flexibility (AI) with control (engineering)
Continuous iteration based on real usage, failures, and feedback
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