Knowledge Engineering Senior Manager- Talent and Workforce (All Genders)
Remote • Kronberg, Campus Kronberg 1
Posted 2d ago
Job Location
Kronberg, Campus Kronberg 1
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Engineer
About the job
Shape the future of enterprise AI by leading Knowledge Graph strategy, architecture, innovation, and delivery across our most complex programs. You will own how demanding programs formulate real-world problems into scalable AI and KG solutions, setting strategy and architecture end to end. You will lead and develop teams of engineers, building capability across the discipline and guiding adoption of new methods and algorithms. You will define what staying at the forefront means for the practice, drive innovation, and translate it into new offerings. You will set the standards for how ontologies are designed, evaluated, and maintained across programs, and make the case to senior stakeholders, shaping the methodologies and data architectures that prove value at scale. You will lead the creation of thought leadership, innovation, and reusable assets that advance the discipline beyond any single engagement, partnering with business and technical leaders to direct end-to-end delivery across complex, multi-stakeholder programs.
Responsibilities
- Lead the complete Knowledge Graph solution scope that transforms data architecture for strategic and complex clients.
- Own the design, development, and implementation of AI and semantic solutions across programs.
- Partner with project leaders, delivery leads, and senior client stakeholders to create stand-out, graph-powered offerings.
- Develop trusted-advisor relationships with senior client stakeholders.
- Make and defend the business case for the semantic layer solution at the executive level.
- Lead sales and pre-sales efforts and shape data transformation programs.
- Drive the practice's thought leadership, innovation, and asset development on trends and agentic technologies, and develop the teams who deliver them.
Requirements
- Bachelor's degree or equivalent.
- Significant professional experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL), schema design, ontology management, and KG curation.
- Considerable experience designing and developing KG solutions and graph-based ML models.
- Experience with end-to-end data pipeline implementations for AI applications (esp. LLMs), with hands-on design and configuration.
- Strong knowledge and experience with relational databases, object stores, graph databases (Stardog, Neo4J, Amazon Neptune), and vector databases.
- Managerial experience leading people.
- Proven track record in sales and/or pre-sales and in delivering data transformation programs and developing teams.
- Experience in Practical experience with NLP techniques and/or Search Techniques, prompt engineering.
- Experience with LLMs for enterprise-scale applications.
- Hands-on experience with cloud platforms (AWS, Azure, GCP).
- Experience in Python, with experience in frameworks like Tensorflow, PyTorch, and tools for building ETL pipelines (e.g. Apache NiFi, Airflow).
- Strong collaboration skills with the ability to work across engineering, research, and product teams across multiple time zones.
- External client-facing consulting experience.
- Ph.D. in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.
- Broad experience in diverse ML techniques and agentic systems.
Benefits
- Performance Equity
- Flexible working models including home office
- Access to over 30,000 training opportunities covering professional and soft skills