Careers

Codeworks, an LRS company, is seeking a Metadata Taxonomist for a Contract opportunity. This role offers the chance to apply your content strategy and UX writing skills in support of meaningful, user‑focused work for one of our client partners.

We are an HR team defining AI solutions for the home office workforce.

The Taxonomist/Metadata Specialist role is the lead specialist and SME for the initiative to standardize and govern metadata across strategic HR content platforms and the core HR management system. The role is responsible for ensuring a consistent, trusted data foundation for AI-driven experiences. This hands-on, execution-oriented role balances theory with delivery to define and operationalize metadata practices for the HR domain that materially improve findability, reuse, and AI and search experience outcomes in production systems.

Top 3-4 must-have skills?

Hands-on taxonomy/metadata development across enterprise platforms (scope, design, validation, launch) especially to improve findability and reuse for AI/search experiences

Metadata governance design & operationalization (standards, templates, approval workflows, and rules to maintain integrity over time)

Stakeholder facilitation and alignment (eliciting domain knowledge, reconciling competing mental models)

Independent, delivery-oriented execution in a greenfield/less mature environment driving production-ready outcomes

Top 3-4 nice-to-have skills?

Familiarity with knowledge graph and graph databases, semantic technologies

Experience with metadata management/governance processes and tools (e.g., Collibra, Informatica, Atlan) and enterprise search/content management system ecosystems

Data management fundamentals (catalog/inventory, lineage concepts, classification practices) and comfort advising on enabling technologies to support metadata standards

Measurement/optimization mindset using search logs, content audits, and consumption analytics to refine metadata models

Key Responsibilities

Analyze existing metadata structures across HR information systems and HR content platforms to identify gaps, overlaps, and inconsistencies.

Define the overall metadata, ontology, and classification strategy for HR content and data to support AI use cases and experiences.

Develop and operationalize for sustainability a comprehensive, HR-wide metadata framework tailored to AI-driven search, retrieval, and AI user experiences including future-state agentic experiences.

Define operational rules, standards, and governance processes (including approval workflows) to maintain metadata integrity over time.

Establish and govern metadata standards including catalog/inventory, lineage, and classification practices in partnership with cross-functional stakeholders.

Collaborate with content strategists, business partners, and IT teams to create and sustain classification systems and taxonomies.

Partner with technology teams to align metadata with underlying AI infrastructure and implementation needs.

Lead and/or consult on the design of activities for co-creation workshops with key stakeholders to gather input on metadata standardization and validate/refine taxonomy and metadata models.

Drive education, documentation, and best practices in partnership with change management partners on tagging practices and metadata.

Consult with technology partners to define and evolve an HR ontology for HR AI systems and experiences and advise on potential technologies (existing and emerging) that can support metadata standardization across HR platforms and systems.

Elicit domain knowledge from HR SMEs, policy owners, call center leads, and other key stakeholders to apply to the HR metadata framework.

Audit real content, search logs, and data from consumption models to apply to framework and to validate usefulness and make iterative, evidence-based adjustments.

Establish pragmatic governance that balances control with adoption, including sunset criteria and change thresholds.

Serve as a single-practitioner taxonomist/metadata lead, setting standards, templates, and repeatable processes without reliance on a large taxonomy team.

Key Deliverables

A fully documented, unified HR-wide standardized metadata framework.

Operational governance guidelines, standards, and workflows for maintaining and evolving metadata.

Training materials and stakeholder education sessions on tagging and metadata usage.

Workshop outcomes, including documented stakeholder feedback on gaps, overlaps, and concerns.

An HR ontology developed in collaboration with key stakeholders.

A roadmap for implementation of metadata standardization and ongoing refinement and adaptation of taxonomy to future AI initiatives to ensure sustainability.

A documented technology advisory report outlining recommended tools or platforms to support metadata standardization.

Minimum Qualifications

Bachelor's degree in information science, library science, semantics/ontology, or a related field (or equivalent practical experience).

2+ years of experience in a metadata-related field (taxonomy, ontology, semantics, computational linguistics), including creating, implementing, and governing taxonomies.

Demonstrated experience building and working with metadata, taxonomy, or ontologies in support of AI-enabled experiences in an enterprise environment including scoping, design, validation, and launch.

Hands-on experience implementing taxonomies or standardizing metadata in a CMS and/or enterprise search platform (not purely academic or archival work).

Experience working directly with business SMEs to reconcile competing mental models into a single controlled vocabulary.

Ability to operate independently in a greenfield environment and drive work to tangible, production-ready outcomes.

Strong facilitation and decision-making skills to prevent analysis paralysis and over-engineering.

Excellent written and verbal communication skills, with the ability to influence and coach stakeholders on metadata standardization value and design.

Strong interpersonal skills and ability to navigate organizational networks and drive alignment across teams.

Awareness of industry trends and standards (knowledge graphs, semantic technologies, graph databases) and advise on relevant applications.

Preferred Qualifications

Experience in highly mature FAANG-style taxonomy environments is acceptable but must be paired with demonstrated success operating as a solo or small-team practitioner in less mature organizations, with limited tooling and evolving governance.

Familiarity with graph databases and semantic/knowledge graph technologies.

Ability to create processes and tools to establish, maintain, and update ontology, taxonomy, and metadata models.

Knowledge of data management principles and technology to support metadata and ontologies (e.g., Informatica, Collibra, Atlan, Microsoft Power BI) and enterprise search/content management and HR data ecosystems (e.g., Lucidworks, Optimizely, ServiceNow, Workday).

Must Have

Information Architecture, Metadata & Taxonomy Application

AI-ready content infrastructures

Demonstrated effective stakeholder management

Metadata Standards

Nice to Have

Ontology & Semantic Modeling (Applied, Lightweight)

knowledge graphsCodeworks, an LRS company, is an equal opportunity employer. Applicants for employment will receive consideration without unlawful discrimination based on race, color, religion, creed, national origin, sex, age, disability, marital status, gender identity, domestic partner status, sexual orientation, genetic information, citizenship, status or protected veteran status.

In some cases, Codeworks, an LRS company, uses generative artificial intelligence (“AI”) in support of our hiring processes. Codeworks takes steps to ensure the use of AI does not result in discrimination based on protected class(es). AI may be used in the hiring process solely in support of the assessment of candidate qualifications. All decisions in the hiring process are made by LRS employees. If AI will be used in the hiring process for the position for which you are applying, you will be notified and will have the opportunity to opt out. Please contact AI.Questions@lrs.com with any questions.

The base range for this contract position is $50.00 - $65.00 per hour, depending on experience. The range displayed reflects the minimum and maximum target for new hires of this position across all U.S. locations. Individual pay is determined by work location and additional job-related factors.

Colorado Pay Range:
50.00 - 65.00/per Hour