PointClickCare

Principal AI Engineer

PointClickCare

full-time

Posted on:

Origin:  • 🇺🇸 United States • Utah

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Salary

💰 $167,400 - $204,600 per year

Job Level

Lead

Tech Stack

CloudPythonSaltStack

About the role

  • The Principal AI Engineer leads the architecture and delivery of agentic AI systems across multiple products, defining technical standards and reusable patterns for reasoning, tool use, and coordinated action.
  • Partner with cross-functional teams to transition prototypes into secure, observable production solutions and establish playbooks, evaluation frameworks, and platform components to accelerate adoption.
  • Drive enterprise-wide AI enablement by defining strategy, evangelizing adoption, and delivering measurable business impact.
  • Identify and prioritize high-value AI use cases, build scalable platforms, and create playbooks and patterns to accelerate implementation.
  • Set the technical vision and reference architecture for agentic AI across products—defining org‑wide standards for reasoning loops, tool use/function calling, memory, safety, and interoperability.
  • Build and govern reusable platform components—model broker & multi‑model routing, orchestration services, evaluation harnesses, prompt/versioning stores, and telemetry—to accelerate adoption across teams.
  • Drive cross‑functional roadmaps and integration standards with Product, Engineering, Architecture, Advanced Tech, and SaaS Ops—setting API/versioning contracts, optimizing LLM/agent cost‑performance, and mentoring engineers to raise the bar.

Requirements

  • Proven leadership shipping agentic AI at scale across multiple products, setting organization‑wide standards for reasoning loops, tool use/function calling, memory, safety, and interoperability.
  • Healthcare & regulatory context: familiarity with HIPAA, ONC‑aligned practices, and clinical workflows for safe deployment in regulated environments.
  • Master’s degree or higher in Artificial Intelligence.
  • Evaluation leadership: establishes offline/online evaluation methodologies for agent behavior and safety, with dashboards tied to business outcomes.
  • Advanced Python expertise for production systems (testing, packaging, performance profiling) and deep experience extending agent frameworks such as LangChain, LangGraph, AutoGen, CrewAI, and/or LlamaIndex.
  • Model serving and cost/perf optimization: experience with model broker patterns, multi‑model routing, and serving stacks.
  • RAG/agent data pipeline expertise: document preprocessing (OCR/NER), chunking strategies, embeddings, vector stores, and data quality/versioning—with evaluation harnesses for quality, cost, and latency.
  • Security & Responsible AI by design: hands‑on implementation of RBAC, audit logging, privacy controls, and alignment with NIST AI RMF and ONC FAVES requirements.