Staff AI Engineer (Knowledge)

Job Summary As an AI Engineer specializing in enterprise knowledge systems, you will architect, implement, and optimize frameworks that enable SCAN to capture, structure, and leverage its collective knowledge. You will design information models, build knowledge graphs, develop AI‑powered retrieval and discovery platforms, and integrate advanced semantic, vector, and hybrid search technologies to support analytics, automation, and decision intelligence across the organization. Essential Job Functions Design and implement frameworks, models, and standards for enterprise knowledge architecture, extending and maintaining taxonomies, ontologies, glossaries, and metadata repositories. Partner with Data Governance to oversee lifecycle processes, standardization, and improve discoverability and reuse of knowledge assets. Build and maintain enterprise knowledge graph platforms, modeling entities and relationships across business domains and technology stacks (Databricks, Snowflake, Azure). Integrate knowledge graphs with AI, analytics, and enterprise applications, ensuring quality and scalability. Architect and implement Retrieval‑Augmented Generation (RAG) platforms and AI‑ready knowledge repositories, designing intelligent retrieval systems using hybrid search and document processing pipelines. Support the development of AI assistants and enhance LLM integration for grounded, accurate responses. Build and maintain pipelines for knowledge ingestion and integration from diverse enterprise sources, implementing metadata extraction, entity resolution, and semantic linking for trusted, governed assets. Design and implement enterprise search and discovery platforms with semantic and AI‑powered capabilities, enabling federated, hybrid, and personalized search experiences. Continuously improve search relevance, ranking, and self‑service access through feedback and measurement. Collaborate across business, data, and technology teams to drive standardization, governance, and innovation, empowering the enterprise to unlock value from its information. Qualifications Bachelor’s Degree or equivalent experience in Computer Science, Engineering, or 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 programming skills in Python (or equivalent) and experience with REST APIs, ML/LLM‑Ops tooling, and frameworks such as FastAPI, LangChain, Semantic Kernel. Ability to structure and connect information into reusable assets, improve content discoverability, and enable efficient retrieval and reuse. Collaborative communicator comfortable engaging non‑technical stakeholders and cross‑functional teams. Commitment to Responsible AI practices—traceability, explainability, fairness, bias detection, and monitoring pipelines. Demonstrated curiosity, initiative, and continuous learning, with the ability to adapt quickly to new frameworks and technologies. Strong business partnering skills, self‑direction, and influence; able to define roadmaps, persuade skeptics, and drive adoption of new processes or technologies. Preferred Experience 6+ years in enterprise knowledge management, information architecture, data engineering, enterprise search, or AI‑powered systems, ideally within regulated industries such as healthcare. 3+ years hands‑on expertise with knowledge graphs, semantic technologies, Retrieval‑Augmented Generation (RAG), and AI‑ready knowledge repositories. Proven track record delivering enterprise‑scale knowledge or AI transformation initiatives, including cross‑functional collaboration with business, healthcare, data, and technology teams. Experience building production‑grade knowledge graph platforms and integrating them with analytics, search, and AI applications. Familiarity with Azure AI Foundry, Azure OpenAI, and PKM tools (Obsidian, Logseq, Roam Research) highly valued. Strong stakeholder management and communication skills, with ability to translate business knowledge into scalable models and drive adoption across diverse teams. Domain expertise in healthcare, including regulatory and member‑focused nuances, a plus. Preferred Certifications Microsoft Certified: Azure AI Engineer Associate Certifications in Knowledge Management, Information Architecture, Data Engineering, or AI (e.g., Certified Knowledge Manager, TOGAF, DAMA). Relevant cloud platform certifications (Azure, AWS, GCP) or enterprise content management. Certifications in Responsible AI, Data Governance, or Healthcare Informatics advantageous. Professional memberships (e.g., DAMA, KMWorld) beneficial. Benefits Base Salary Range: $106,200 to $182,983 annually. Annual employee bonus program. Robust wellness program. Generous paid‑time‑off and 11 paid holidays per year, 1 floating holiday, birthday off, and 2 volunteer days. Excellent 401(k) retirement saving plan with employer match. Robust employee recognition program. Tuition reimbursement. Equal Employment Opportunity Statement SCAN is a proud Equal Employment Opportunity and affirmative action workplace. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, age, sex (including pregnancy, childbirth or related medical conditions), sexual orientation, gender identity or expression, disability, protected veteran status, or any other status protected by law. A background check is required. #J-18808-Ljbffr GRP SCAN Group