Applied AI Engineer

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).