Job Description

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 caredelivering 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 Youll 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 Were 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 Youll 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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