Applied AI Engineer at Pager Health

Pager Health seeks a builder to develop production-grade LLM-powered agent systems. This is a hands-on engineering role focused on translating specifications into robust, deployable services rather than research work. You will handle the complete lifecycle from prototyping through production deployment.

Responsibilities

Build agentic applications and workflows using LLM frameworks and guardrails

Implement tool integrations and orchestration logic across internal and external APIs

Deploy RAG pipelines with vector store integration and optimization

Own full lifecycle from prototype through production monitoring

Build evaluation infrastructure to measure agent quality, latency, and safety

Collaborate with data science and infrastructure teams

Deploy services across GCP/Vertex AI, AWS Bedrock, and Azure OpenAI

Requirements

3+ years software engineering with Python proficiency

Hands-on LLM application development (Claude, GPT, Gemini)

Agent framework experience (LangChain, LangGraph, CrewAI, or similar)

RAG architecture and vector database knowledge (Pinecone, Weaviate, pgvector)

Cloud deployment experience (GCP/Vertex AI, AWS Bedrock, Azure)

Function calling and multi-step workflow implementation

API design and microservices deployment

Nice-to-have: MLOps, CI/CD, evaluation frameworks (RAGAS, LangSmith), GCP/Vertex AI expertise.

Compensation: $150,000 - $160,000 plus equity and benefits (for CO, NV, NY, DC).