Software Engineer, AI Systems
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Before you apply
LocationHQ
Work modehybrid
Typefull-time
SenioritySenior
Experience5+ yrs
DepartmentEngineering
Company size8+ people
PostedMar 18, 2026 · 7mo ago
Verified live1d ago
May no longer be actively hiring
Posted by the company on Mar 18, 202655% of this company's open roles have been listed for 90+ days
At a glanceSummarised by Seekless from the posting.
5+ years of professional software engineering experience, including building and operating AI production systems.
Strong backend engineering skills and experience making architecture decisions for substantial technical projects.
Deep experience in at least one of these areas: production AI agents and orchestration, or ML pipelines, evaluation, and feedback systems.
Hands-on experience with LLM-based applications and understanding of their behavior and limitations.
Ability to investigate failures across multiple components and use evidence to guide improvements.
Interest in working across live agent systems and offline evaluation and learning pipelines.
Experience with voice or conversational AI.
Experience building platforms or frameworks used by other engineers.
Experience with post-training, fine-tuning, or training data development.
Experience turning research prototypes into reliable production systems.
Skills
Python
LLM
AI
ML
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 and helps providers focus on those who need them most 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 Software Engineer to develop the systems behind our AI agents and turn production conversations into measurable improvements.
The work spans two areas: building agent platform that makes patient workflows easy to develop and adapt across healthcare partners, and building evaluation and ML pipelines that help us understand failures and improve agent behavior.
You’ll work closely with our engineers and researcher. We welcome depth in either area and a desire to develop the other. Your initial focus will reflect your strengths and the team’s needs.
We welcome senior and staff-level engineers. Scope and responsibilities will reflect your experience.
What You’ll Do
•
Design and build agent systems for increasingly complex workflows, including scheduling and medication refills.
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Develop reusable approaches to orchestration, tool use, conversation state, and recovery that support differences across healthcare partners.
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Build pipelines that analyze production conversations, identify recurring failures, and generate useful evaluation datasets.
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Develop evaluations that measure agent quality and catch regressions across models, prompts, and orchestration.
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Translate findings into production improvements and verify their impact.
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Work with research to bring promising techniques into production, making practical tradeoffs across quality, latency, and cost.
What We’re Looking For
Required
•
5+ years of professional software engineering experience, including building and operating AI production systems.
•
Strong backend engineering skills and experience making architecture decisions for substantial technical projects.
•
Deep experience in at least one of these areas: production AI agents and orchestration, or ML pipelines, evaluation, and feedback systems.
•
Hands-on experience with LLM-based applications and understanding of their behavior and limitations.
•
Ability to investigate failures across multiple components and use evidence to guide improvements.
•
Interest in working across live agent systems and offline evaluation and learning pipelines.
Nice to Have
•
Experience with voice or conversational AI.
•
Experience building platforms or frameworks used by other engineers.
•
Experience with post-training, fine-tuning, or training data development.
•
Experience turning research prototypes into reliable production systems.