Knowledge Engineering Manager
YOU ARE
You lead a significant knowledge engineering scope and function within a large program; actively contribute to thought leadership. You shape how a substantial body of work formulates real-world problems into scalable AI and KG solutions, and set the technical direction for that scope. You lead a team and guide exploration and implementation of new methodologies, model building techniques, and cutting-edge algorithms. You remain at the forefront and drive innovation by applying these techniques to new business problems, use cases, and scenarios. You design, evaluate, and maintain ontologies, and establish the standards others follow. You justify the value to business and technology stakeholders, and construct the methodologies and data architectures that demonstrate it. You publish or present perspective beyond the immediate project. You work across business and technical teams to drive end-to-end delivery for their scope.
THE WORK
Leads the build of Knowledge Graph solutions that transform a client's data architecture within program scope.
Directs the design, development, and implementation of AI and semantic solutions, ensuring all the pieces work together seamlessly.
Works with project leaders, delivery leads, and client stakeholders to create stand-out, graph-powered Data & AI offerings.
Develops strong client relationships and earns the trust of key advisors.
Makes the business case for the semantic layer solution recommended to the client.
Contributes meaningfully to Accenture sales and pre-sales efforts.
Provides thought leadership on technology trends, new opportunities, innovations, and foreseeable limitations, risks, and concerns.
EDUCATION
Bachelor's degree or equivalent
BASIC (REQUIRED) QUALIFICATION
Bachelor's degree or equivalent, plus at least 4 of the following:
Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL)
solid experience in schema design, ontology management, and KG curation
Proven experience in designing and developing KG solutions and graph-based ML models (functional + technical)
Experience with end-to-end data pipeline implementations for AI applications (esp. LLMs), with hands-on design and configuration
Strong knowledge/working experience of relational databases, object stores, graph databases (Stardog, Neo4J, Amazon Neptune), and vector databases
London
Berlin
Madrid
Paris
平等就业机会声明
所有聘用决定均不考虑年龄、种族、信仰、肤色、宗教、性别、国籍、血统、残疾状况、退伍军人身份、性取向、性别认同或表达、基因信息、婚姻状况、公民身份或任何其他受联邦、州或地方法律保护的因素。
求职者在招聘过程中没有义务披露已封存或已删除的定罪或逮捕记录。
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