Talent Ecosystem Specialist
Genesys · Hungary
Be the one building AI-powered experiences where they matter most.
At Genesys, we help organizations create better customer experiences through AI-powered experience orchestration. Our platform connects people, systems, data and AI to help organizations deliver more personalized service, improve operational efficiency and build stronger customer relationships.
Help build, support and operate technology used by more than 8,000 organizations in over 100 countries – moving AI from possibility to production in real-world enterprise environments every day.
We are building the next generation of our Talent & Learning ecosystem—one that connects skills, learning, career mobility, enablement, employee data, and emerging AI capabilities into a more personalized and seamless employee experience.
The Talent Ecosystem Specialist will play a key role in turning this vision into reality.
This role will help design, connect, and continuously improve the technologies, data, processes, and employee experiences that make up our Talent & Learning ecosystem. Working across Talent & Learning, HR Technology, business enablement teams, and technology partners, this position will help move us from a collection of strong but disconnected tools toward a connected, skills-driven, AI-ready talent ecosystem.
This is a hands-on role for someone who enjoys working at the intersection of talent, learning, technology, data, and employee experience. The successful candidate can take an ambiguous problem, understand how people, processes, data, and technology connect, and translate that understanding into practical solutions.
What You’ll Do
- Support the development and ongoing evolution of the enterprise Talent & Learning technology ecosystem across learning, skills, career mobility, enablement, analytics, knowledge, and emerging AI capabilities.
- Build and maintain a comprehensive view of talent and learning technologies, including capabilities, ownership, integrations, data flows, dependencies, usage, and opportunities for improvement.
- Work with HR Technology and platform owners to improve how employee, role, skills, learning, and career data move across systems.
- Help advance a unified employee skill profile by connecting signals from job profiles, employee-entered skills, learning activity, career interests, manager input, certifications, assessments, and approved external sources.
- Support the development and adoption of common skills taxonomy, metadata, tagging, and data-quality standards across the ecosystem.
- Work with learning and enablement teams to make their programs more discoverable through consistent tagging, navigation, and measurement while allowing teams to retain ownership of their programs.
- Identify friction across employee learning and career journeys and recommend opportunities to simplify or connect experiences.
- Translate employee and business needs into requirements, user stories, workflows, data requirements, and technology enhancements.
- Support pilots for personalized learning, skill-gap identification, career recommendations, and other skills-based experiences.
- Establish feedback loops with employees, managers, and stakeholders to evaluate experiences and continuously improve recommendations.
- Coordinate initiatives across Talent & Learning, HR Technology, IT, People Analytics, enablement teams, and technology vendors.
- Support testing, implementation, documentation, communications, and change enablement for ecosystem enhancements.
- Explore emerging AI opportunities while ensuring foundational requirements—including data quality, governance, privacy, transparency, and employee trust—are addressed first.
What You’ll Help Build
The future Talent ecosystem will increasingly enable:
For employees: Personalized learning, skills development, and career opportunities based on their role, skills, interests, experiences, and aspirations.
For managers: Better visibility into team capabilities, development opportunities, emerging skill gaps, and career growth.
For enablement teams: A shared ecosystem through which programs and content can be discovered while teams maintain ownership of their offerings.
For Talent & Learning: Better insight into employee needs, content effectiveness, skills gaps, and where future investment will have the greatest impact.
For leadership: More accurate workforce skills data and stronger signals for talent and workforce planning.
Over time, this connected foundation will also enable responsible AI-powered recommendations, career guidance, manager insights, and conversational employee experiences. This reflects the strategy's progression from connecting foundational signals to enabling richer recommendations and AI experiences.
What You’ll Bring
- 3–5+ years of experience in Learning & Development, Talent Management, HR Technology, Talent Technology, People Analytics, HR Operations, or a related field.
- Experience working with HR, talent, or learning technology platforms and an understanding of how employee experiences span multiple systems.
- Strong ability to translate business and employee needs into technology, process, data, or experience requirements.
- Experience supporting cross-functional initiatives involving multiple stakeholders, technologies, or teams.
- Working knowledge of skills-based talent practices, learning technology, career development, talent marketplaces, or employee experience.
- Comfort working with data to identify trends, gaps, data-quality issues, and opportunities for improvement.
- Experience documenting workflows, requirements, system dependencies, or data flows.
- Strong project management and organizational skills with the ability to manage multiple priorities in an evolving environment.
- Strong written and verbal communication skills, including the ability to make complex technology and data concepts understandable to nontechnical audiences.
- Curiosity about AI and emerging talent technologies, balanced with an understanding of the importance of governance, data quality, and employee trust.
Preferred Qualifications
Experience with one or more of the following is beneficial but not required: Workday Learning, Career Hub, Skills Cloud, TechWolf, LinkedIn Learning, skills taxonomies, learning metadata, HR integrations/APIs, recommendation engines, talent marketplaces, or AI-enabled employee experiences.
Experience with Agile methodologies, user stories, journey mapping, design thinking, or product management practices would also be valuable.
What Success Looks Like
In the first 12–18 months, the Talent & Learning Ecosystem Specialist will help:
- Establish a validated inventory and ownership view of the Talent & Learning technology ecosystem.
- Improve skills, learning metadata, and content-data quality.
- Document and improve critical integrations and signal flows.
- Increase consistency of skill tagging across priority learning and talent experiences.
- Support successful recommendation and employee-experience pilots.
- Establish stronger measurement and employee feedback loops.
- Improve visibility into ecosystem adoption, gaps, and effectiveness.
- Build the data and governance foundation necessary for future AI capabilities.
The broader measure of success is whether employees increasingly experience one connected Talent & Learning ecosystem rather than a collection of separate tools. This directly supports the roadmap of stabilize → standardize → connect → optimize outlined in the strategy.
Why This Role Matters
The future of Talent & Learning isn't about adding more technology. It's about making the technology and data we have work better together.
When learning activity strengthens an employee's skills profile, skills improve learning and career recommendations, enablement activity becomes part of the employee talent picture, and managers gain better workforce insights, the ecosystem becomes more valuable with every interaction.
The Talent Ecosystem Spe