Applied AI Engineer

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🔥 0 minutes ago

⛰️ Colorado, Nevada, +2 more states – Remote

⛰️ Colorado – Remote 🎰 Nevada – Remote 🗽 New York – Remote ☕ Washington – Remote

💵 $150k - $160k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

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Pager Health

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2014

⚕️ Healthcare Insurance

☁️ SaaS

🤖 Artificial Intelligence

Healthcare Insurance • SaaS • Artificial Intelligence

Pager Health is a connected health platform company that enables healthcare enterprises to deliver high-engagement, intelligent health experiences for their patients, members, and teams through integrated technology, AI, and concierge services. Their solutions provide secure access and support proactive, personalized care across the healthcare journey, improving engagement and satisfaction for users.

📋 Description

• Build agentic applications and workflows using LLM frameworks, models, and guardrails provided by the Data Science team • Design and implement tool integrations, function-calling patterns, and orchestration logic • Translate agent specifications and prompt strategies into robust, deployable services • Implement RAG pipelines • Own the full lifecycle of agent systems from prototype through production • Build evaluation and observability infrastructure • Collaborate with Data Science on prompt engineering, model behavior tuning, and guardrail enforcement • Work with platform and infrastructure teams to deploy, scale, and maintain agent services in cloud environments • Contribute to internal tooling, SDKs, and shared libraries

🎯 Requirements

• 3+ years of software engineering experience with strong proficiency in Python • Hands-on experience building applications powered by large language models (Claude, GPT, Gemini) • Familiarity with agent frameworks and orchestration patterns (LangChain, LangGraph, CrewAI, Vertex AI Agent Builder, or custom orchestration) • Experience implementing function calling, tool use, and multi-step agent workflows • Solid understanding of RAG architectures, embedding models, and vector databases (Pinecone, Weaviate, pgvector, Vertex AI Vector Search) • Comfort working within defined guardrails and model configurations • Experience with API design, microservices, and deploying services in cloud environments • Strong debugging and problem-solving instincts • Strong communication skills; ability to work across Data Science, Product, and Engineering teams • Experience with evaluation frameworks for LLM-based systems is nice to have • Familiarity with MLOps tooling and CI/CD for ML systems and experience with streaming responses, async architectures, and real-time agent interactions are nice to have • Background in building multi-agent systems with routing, delegation, and coordination patterns is preferred • Exposure to Google Cloud Platform/Vertex AI ecosystem is preferred • Contributions to open-source AI/ML projects is preferred

🏖️ Benefits

• stock options • a range of medical, dental, vision, financial • generous PTO • stipends for professional development • wellness benefits