Sage Care Inc.
Title:
AI Orchestration Engineer Location:
Hybrid, Palo Alto, CA — Tuesday through Thursday About Us
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. Job Overview
An AI Orchestration Engineer focuses on designing, implementing, and maintaining the “glue” that coordinates multiple AI models, agents, and workflows into a cohesive system. Rather than just building models, this role ensures they interact effectively, scale properly, and integrate seamlessly into real-world applications. 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
AI Orchestration Engineer Location:
Hybrid, Palo Alto, CA — Tuesday through Thursday About Us
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. Job Overview
An AI Orchestration Engineer focuses on designing, implementing, and maintaining the “glue” that coordinates multiple AI models, agents, and workflows into a cohesive system. Rather than just building models, this role ensures they interact effectively, scale properly, and integrate seamlessly into real-world applications. 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