Job Architecture & Skills Taxonomy

Part of the worlds-biggest-software-project initiative.

An AI-native, open-source toolkit for defining roles, levels, and skills frameworks company-wide — built on open taxonomies so any organisation can adopt skills-based workforce planning without enterprise consulting fees.

Job Architecture & Skills Taxonomy gives HR transformation, total rewards, and L&D teams a structured way to model job families, grade/level hierarchies, and skill requirements, then continuously compare them against employee profiles. It is aimed at mid-market and SMB organisations that today have no affordable path to skills-based job architecture, and grounds its data in the Lightcast Open Skills taxonomy (CC-BY) and O*NET (US public domain) rather than proprietary ontologies.

Why Job Architecture & Skills Taxonomy?

Consulting-grade work is locked behind enterprise budgets. Korn Ferry and Mercer charge $200K–$1M+ per engagement to build a job architecture; most firms below the Fortune 1000 simply go without.
Enterprise software is no cheaper. Gloat ($150K–$500K+/year), Beamery ($200K–$600K+/year), and Lightcast data access ($50K–$300K+/year) all target large enterprises and bundle proprietary ontologies that cannot be exported.
Open data exists, but no open tooling. O*NET is public domain and the Lightcast Open Skills taxonomy is CC-BY, yet no open-source builder ties them into a usable job architecture workflow with grade/level hierarchies and gap analysis.
Static taxonomies decay quickly. WEF Future of Jobs 2025 estimates 39% of existing skill sets will be outdated by 2030; manually-curated frameworks go stale within 18 months and emerging roles take 2–3 years to land in O*NET.
The demand is acute. 63% of employers in the WEF 2025 survey cite skill gaps as the top barrier to business transformation, and 45% of large enterprises report moving to skills-based job architecture in 2025.

Key Features

Open Taxonomy Foundation

Import and search the Lightcast Open Skills taxonomy (32,000–34,000 skills, CC-BY 4.0) as the default skills library.
Bundle O*NET occupational data (1,000+ occupations, US public domain) for role and task descriptors.
Optional ESCO multilingual data (CC-BY 4.0) for non-English skill display across 27 languages.
Crosswalk mappings between Lightcast, O*NET, and ESCO for interoperability with existing HR tooling.

Job Architecture Builder

Job profile builder for defining roles with skill requirements and proficiency levels.
Grade/level hierarchy builder supporting job families, levels, and pay banding — the structural core of any job architecture project.
Career pathway visualisation showing progression routes through the architecture.
Export to standard formats (CSV, JSON, HR-XML) for downstream HRIS import.

Skills Gap Analysis

Compare employee profiles (uploaded or HRIS-synced) to role requirements with visual gap heat maps.
Aggregate organisational skills heat maps showing capability coverage and gaps across teams and business units.
Optional Lightcast API integration to overlay external market demand and salary benchmarks against internally-defined roles.

Integration & Interchange

CSV import/export at minimum, with API connectors for HRIS systems such as Workday and BambooHR.
HR-XML / JSON interchange schemas for exchanging job profiles and competency data with other systems.
API-first design so the taxonomy and architecture data can be consumed by ATS, LMS, and talent marketplace tools.

AI-Assisted Curation (v1.1+)

AI-assisted role profiling: given a job title and description, auto-suggest skills and proficiency levels drawn from the open taxonomy.
Self-maintaining taxonomy agent that monitors external sources to propose emerging skills for addition and obsolete skills for deprecation.
Organisational capability risk surfacing — aggregating skills gaps to flag systemic risks (e.g. a complete absence of a critical capability) and recommend build/buy/partner responses.

AI-Native Advantage

Most incumbent taxonomies are either static (O*NET) or proprietary and locked to a single platform (Gloat, Beamery). An AI-native approach lets the taxonomy continuously parse job postings, profiles, and course catalogues to keep skills current without manual curation, and lets organisations generate a credible first-draft job architecture from job postings and incumbent data instead of a multi-month consulting engagement. AI also enables natural-language role definition and organisation-wide capability risk detection — capabilities today's tools either gate behind enterprise pricing or do not offer at all.

Tech Stack & Deployment

The project is intended as self-hostable open-source software with optional cloud deployment. It builds on the Lightcast Open Skills taxonomy (CC-BY 4.0), O*NET (US public domain), and ESCO (CC-BY 4.0), with crosswalks between them. Integration is API-first, with HRIS connectors (Workday, BambooHR), HR-XML / JSON interchange, and optional Lightcast API access for live labour-market signals. SFIA and the WEF Global Skills Taxonomy are candidates for plug-in extension to support IT-specific and global workforce-planning use cases.

Market Context

The global skills management and talent intelligence market was approximately $3.5B in 2024 and is projected to reach $7.5B by 2030 (CAGR ~13%). Incumbent pricing ranges from $5–$10 PEPM at the SMB career-pathing tier (Fuel50) up to $150K–$600K+/year for enterprise platforms (Gloat, Beamery), with Lightcast data access at $50K–$300K+/year on top. Primary buyers are Compensation & Total Rewards teams, HR Transformation Leads, L&D Directors, and CHROs/CPOs driving skills-based workforce strategy.

Project Status

This project is in the research and specification phase.
Contributions, feedback, and domain expertise are welcome.

Contributing

We welcome contributions from developers, domain experts, and potential users. See CONTRIBUTING.md for guidelines.

Important: All contributions must be your own original work or clearly attributed open-source material with a compatible licence. Copyright infringement and licence violations will not be tolerated and will result in immediate removal of the offending contribution. If you are unsure whether a piece of code, text, or other material is safe to contribute, open an issue and ask before submitting.

Licence

Licence to be determined. See discussion for context.