Sage Care
Title:
AI Orchestration Engineer Location:
Hybrid, Palo Alto, CA — Tuesday through Thursday Overview
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. What You’ll Do
Workflow & Pipeline Orchestration Build and manage directed workflows (DAGs, state machines, LangGraph flows) Define how data and context move between AI models, APIs, and humans in the loop Multi-Agent Collaboration Design coordination strategies for multiple AI agents with specialized roles Implement arbitration logic to merge outputs, resolve conflicts, and dynamically route tasks Integration & Infrastructure Connect AI systems with vector databases, APIs, cloud platforms, and external data sources Handle orchestration across distributed environments (Kubernetes, serverless) Reliability & Error Handling Implement retries, fallbacks, and guardrails to keep workflows stable Ensure systems degrade gracefully when AI outputs are uncertain or incorrect Optimization & Evaluation Tune orchestration for cost, latency, and accuracy Build observability dashboards, logging, and metrics to measure workflow success Example Use Cases You Might Work On
Routing patient triage queries across different AI agents (diagnosis, risk scoring, recommendations) Coordinating a retrieval-augmented generation (RAG) pipeline: retriever → ranker → LLM Running human-in-the-loop workflows where AI suggests and humans validate Ensuring continuity across multi-step processes, such as decision trees for medical protocols What We’re Looking For
Programming: Proficiency in Python, TypeScript, or Go (depending on orchestration stack) Frameworks: Experience with LangGraph, LangChain, or Ray Infrastructure: Strong knowledge of Docker, Kubernetes, CI/CD pipelines, and observability tools (Prometheus, Grafana) AI/ML Understanding: Familiarity with LLMs, RAG systems, embeddings, and multi-agent patterns Data Systems: Experience with vector databases (FAISS, Pinecone, Weaviate) and caching systems (Redis, Memcache) Nice to Have
Hands-on experience with healthcare workflows or regulated environments Exposure to human-in-the-loop AI systems Background in reliability engineering or distributed systems Why You’ll Love Working Here
Mission-driven work at the intersection of AI and healthcare Collaborative team that values curiosity, creativity, and ownership Flexibility to experiment with the newest orchestration frameworks and AI infrastructure
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AI Orchestration Engineer Location:
Hybrid, Palo Alto, CA — Tuesday through Thursday Overview
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. What You’ll Do
Workflow & Pipeline Orchestration Build and manage directed workflows (DAGs, state machines, LangGraph flows) Define how data and context move between AI models, APIs, and humans in the loop Multi-Agent Collaboration Design coordination strategies for multiple AI agents with specialized roles Implement arbitration logic to merge outputs, resolve conflicts, and dynamically route tasks Integration & Infrastructure Connect AI systems with vector databases, APIs, cloud platforms, and external data sources Handle orchestration across distributed environments (Kubernetes, serverless) Reliability & Error Handling Implement retries, fallbacks, and guardrails to keep workflows stable Ensure systems degrade gracefully when AI outputs are uncertain or incorrect Optimization & Evaluation Tune orchestration for cost, latency, and accuracy Build observability dashboards, logging, and metrics to measure workflow success Example Use Cases You Might Work On
Routing patient triage queries across different AI agents (diagnosis, risk scoring, recommendations) Coordinating a retrieval-augmented generation (RAG) pipeline: retriever → ranker → LLM Running human-in-the-loop workflows where AI suggests and humans validate Ensuring continuity across multi-step processes, such as decision trees for medical protocols What We’re Looking For
Programming: Proficiency in Python, TypeScript, or Go (depending on orchestration stack) Frameworks: Experience with LangGraph, LangChain, or Ray Infrastructure: Strong knowledge of Docker, Kubernetes, CI/CD pipelines, and observability tools (Prometheus, Grafana) AI/ML Understanding: Familiarity with LLMs, RAG systems, embeddings, and multi-agent patterns Data Systems: Experience with vector databases (FAISS, Pinecone, Weaviate) and caching systems (Redis, Memcache) Nice to Have
Hands-on experience with healthcare workflows or regulated environments Exposure to human-in-the-loop AI systems Background in reliability engineering or distributed systems Why You’ll Love Working Here
Mission-driven work at the intersection of AI and healthcare Collaborative team that values curiosity, creativity, and ownership Flexibility to experiment with the newest orchestration frameworks and AI infrastructure
#J-18808-Ljbffr