Knowledge Engineer

About Avalon Healthcare Solutions: Avalon Healthcare Solutions is the nation’s leader in diagnostic intelligence, uniquely focused on transforming the role of diagnostic testing across the healthcare ecosystem. Our proprietary Diagnostic Insights Platform delivers evidence-based policies, curated lab networks, and real-time analytics that simplify complex diagnostics, accelerate innovation adoption, and optimize diagnostic investments. Supporting over 30 health plans and 100 million members nationwide, Avalon partners with payers and providers to ensure diagnostic testing is performed appropriately, efficiently, and at the right time. Our flexible solutions span routine and genetic testing management, automated adherence, and end-to-end diagnostics support—driving measurable value, reduced waste, and improved clinical outcomes. With unmatched scientific rigor, deep clinical expertise, and a performance-based model, Avalon is redefining how diagnostics power personalized care and healthcare value. You will be part of a team that shapes a new market and business. Most importantly, you will help Avalon to achieve its mission and improve clinical outcomes and health care affordability for the people we serve. For more information about Avalon, please visit www.avalonhcs.com Avalon Healthcare Solutions is an Equal Opportunity Employer - Vet/Disability. This position description is subject to change at any time. As determined by the company based upon business needs, an employee in this position may be required to perform duties and take responsibility for work other than as described in this document. About the Knowledge Engineer Position: Within the Applied Intelligence department, the Knowledge Engineer is the bridge between the business and Avalon’s agentic AI systems. The Knowledge Engineer works directly with departments across the enterprise to elicit and document data, business rules, workflows, and institutional knowledge and translate that material into business glossaries, taxonomies, semantic models, and context artifacts that AI agents can reliably consume. The Knowledge Engineer also owns the audit side of this work: designing audit logic and test sets that measure agent accuracy, identifying defects and root causes, and reporting results to business and technical stakeholders. Partnering with data and AI teams, this role ensures agents answer questions with the right context, definitions, and guardrails while maintaining auditable, current knowledge assets. This position is eligible for remote work, but quarterly travel will be required to Avalon's corporate office located in Tampa, Florida. Knowledge Engineer – Essential Functions and Responsibilities: Partner with business owners, clinical subject matter experts, and operational leaders across the enterprise to elicit and document the data, business rules, processes, and decision logic behind their work through interviews, workshops, and process walkthroughs Produce current-state and future-state process documentation, workflow maps, and decision trees that make undocumented institutional knowledge explicit and reviewable Translate business, clinical, and regulatory requirements into structured, machine-readable artifacts including business glossaries, metric and metadata definitions, taxonomies, semantic models, and decision rules Contribute to the semantic layer and context artifacts that agentic AI systems consume, including Snowflake semantic views, verified queries, and the metadata used by Cortex AI and Snowflake Intelligence Coordinate unstructured and semi-structured content for ingestion, chunking, and retrieval by AI agents Reconcile conflicting definitions, naming, and business logic across departments and drive them to a single agreed-upon source of truth Assist in the definition and document agent scope, guardrails, and escalation paths Design and maintain SQL-based audit logic, evaluation sets, and gold-standard question and answer pairs used to measure agent accuracy, groundedness, and completeness Audit agent output against business and clinical expectations, identify defects, perform root cause analysis, and remediate underlying context Build reporting and dashboards in Power BI, Tableau, or Streamlit that make agent performance, knowledge coverage, and audit findings visible Maintain a versioned, auditable knowledge base with change management, lineage, and named business ownership Collaborate with Snowflake engineers to specify data ingestion, structure, and access requirements Identify opportunities to reduce manual effort across the business by applying agentic and automation capabilities Assist in the development of pilots, proofs of concept, and production releases of AI agents, data science products and services, and other knowledge-driven applications Develop training materials and lead sessions that teach business users how to work with agentic tools Collaborate with team members on several projects at once Employ strong analytical and organizational skills and attention to detail Knowledge Engineer – Minimum Qualifications: Extensive experience eliciting requirements and documenting business processes, business rules, reporting logic, and data definitions in partnership with non-technical and clinical stakeholders Demonstrated ability to translate complex clinical, operational, and regulatory requirements into practical, well-documented solutions Strong, hands-on SQL skills with the ability to profile, query, audit, and validate data independently Experience developing audit, quality measurement, or defect identification logic Experience creating process flow, workflow, and current-state/future-state documentation Experience building reporting or dashboards in tools such as Power BI, Tableau, or SSRS Superior written communication and documentation skills Excellent facilitation and interviewing skills Working understanding of large language models and agentic AI concepts Ability to work with ambiguity, structure undefined problems, and drive decisions to closure Desire to learn new software, techniques and methods Knowledge Engineer – Preferred Qualifications: Healthcare experience – pharmacy, managed care, health plans, hospitals, pharmaceutical Experience with medical and lab claims, lab results, eligibility, utilization management, or prior authorization data and workflows Experience with Snowflake, including semantic views, Cortex AI, and Snowflake Intelligence Hands-on experience building business glossaries, taxonomies, ontologies, semantic models, metadata catalogs, or knowledge graphs Experience with prompt design, retrieval-augmented generation, or evaluation frameworks for AI products Experience in data governance, master data management, or data stewardship Experience designing or delivering training, enablement, or knowledge transfer programs Experience with quality reporting or accreditation programs such as HEDIS, Stars, NCQA, or URAC Background in management information systems, healthcare or clinical informatics, information science, or business process analysis Experience with advanced analytics