Staff AI Engineer (Knowledge

AI Engineer Specializing In Enterprise Knowledge Systems

Founded in 1977 as the Senior Care Action Network, SCAN began with a simple but radical idea: that older adults deserve to stay healthy and independent. That belief was championed by a group of community activists we still honor today as the "12 Angry Seniors." Their mission continues to guide everything we do.

Today, SCAN is a nonprofit health organization serving more than 500,000 people across Arizona, California, Nevada, New Mexico, Texas, and Washington, with over $8 billion in annual revenue. With nearly five decades of experience, we have built a distinctive, values-driven platform dedicated to improving care for older adults.

Our work spans Medicare Advantage, fully integrated care models, primary care, care for the most medically and socially complex populations, and next-generation care delivery models. Across all of this, we are united by a shared commitment: combining compassion with discipline, innovation with stewardship, and growth with integrity.

At SCAN, we believe scale should strengthen—not dilute—our mission. We are building the future of care for older adults, grounded in purpose, accountability, and respect for the people and communities we serve.

As an AI Engineer specializing in enterprise knowledge systems, you will architect, implement, and optimize frameworks that enable the organization to capture, structure, and leverage its collective knowledge. Your responsibilities span designing information models, building knowledge graphs, and developing AI-powered retrieval and discovery platforms. By integrating advanced semantic, vector, and hybrid search technologies, you will ensure that knowledge assets are discoverable, reusable, and support analytics, automation, and decision intelligence.

You will collaborate across business, data, and technology teams to drive standardization, governance, and innovation—empowering the enterprise to unlock value from its information and accelerate transformation initiatives.

Enterprise Knowledge Management & Information Architecture

• Design and implement frameworks, models, and standards for enterprise knowledge architecture.
• Extend and maintain taxonomies, ontologies, glossaries, and metadata repositories beyond data to policies and procedures, business behaviors, and other undocumented sources.
• Partner with Data Governance on oversight, lifecycle processes, and standardization to improve discoverability and reuse of knowledge assets.

Knowledge Graph Engineering

• Build and maintain enterprise knowledge graph platforms, modeling entities and relationships across business domains and technology stacks (Databricks, Snowflake, Azure).
• Partner with Data Governance and Engineering on semantic data models, graph schemas, and enable graph-based discovery and navigation.
• Integrate knowledge graphs with AI, analytics, and enterprise applications, ensuring quality and scalability.

AI-Powered Knowledge Systems & Retrieval-Augmented Generation (RAG)

• Architect and implement RAG platforms and AI-ready knowledge repositories.
• Design intelligent retrieval systems using hybrid search and document processing pipelines.
• Support development of AI assistants and enhance LLM integration for grounded, accurate responses.

Knowledge Integration & Data Engineering

• Build and maintain pipelines for knowledge ingestion and integration from diverse enterprise sources.
• Implement metadata extraction, entity resolution, and semantic linking for trusted, governed assets.
• Collaborate with data engineering teams to ensure quality, lineage, and master/reference data integration.

Enterprise Search & Knowledge Discovery

• Design and implement enterprise search and discovery platforms with semantic and AI-powered capabilities.
• Enable federated, hybrid, and personalized search experiences across repositories and systems.
• Continuously improve search relevance, ranking, and self-service access through feedback and measurement.
• We seek Rebels who are curious about AI and its power to transform how we operate and serve our members.
• Actively support the achievement of SCAN's Vision and Goals.
• Other duties as assigned.

• Bachelor's Degree or equivalent experience in Computer science, Engineering, or a related field
• Deep applied understanding of LLM-based architectures, retrieval-augmented generation (RAG), vector embeddings, prompt engineering, and agent orchestration
• Expertise in knowledge graph design, semantic modeling, ontology engineering, and metadata management.
• Proficiency with Azure AI Services, Azure AI Foundry, and enterprise content management platforms (SharePoint, Microsoft 365, Teams, Confluence).
• Strong Python (or equivalent), REST APIs, ML/LLMOps tooling, and frameworks (FastAPI, Lang Chain, Semantic Kernel, etc.).
• Ability to structure and connect information into reusable assets, improve content discoverability, and enable efficient retrieval and reuse.
• Collaborative communicator, comfortable engaging…