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Accenture

Advises businesses and runs their technology

Data Engineer - Knowledge Graphs & AI

Data EngineeringUpdated on Nov 5
Full-timeNo salary listed

About the Job

Requirements

  • A bachelor's degree or equivalent is required.
  • Experience with at least four of the listed qualifications is required: Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL); hands-on schema design, ontology management, and Knowledge Graph curation; designing and developing Knowledge Graph solutions and graph-based machine-learning models; end-to-end data pipeline implementation for AI applications, especially large language models, including hands-on design and configuration; strong knowledge of relational databases, object stores, graph databases such as Stardog, Neo4j, and Amazon Neptune, and vector databases; and leading a team or workstream within a larger program.
  • Fluency in Spanish and a high level of understanding and communication in English (B2–C1) are required.

Responsibilities

  • Lead a significant knowledge-engineering scope and function within a large program and contribute to thought leadership.
  • Shape how a substantial body of work formulates real-world problems into scalable AI and Knowledge Graph solutions, and set the technical direction for that scope.
  • Lead a team and guide exploration and implementation of new methodologies, model-building techniques, and algorithms.
  • Apply new techniques to business problems, use cases, and scenarios to drive innovation.
  • Design, evaluate, and maintain ontologies, and establish standards for others to follow.
  • Justify the value of solutions to business and technology stakeholders, and construct methodologies and data architectures that demonstrate that value.
  • Publish or present perspectives beyond the immediate project.
  • Work across business and technical teams to drive end-to-end delivery for the assigned scope.
  • Lead the build of Knowledge Graph solutions that transform a client's data architecture within the program scope.
  • Direct the design, development, and implementation of AI and semantic solutions.
  • Work with project leaders, delivery leads, and client stakeholders to create graph-powered Data & AI offerings.
  • Develop client relationships and earn the trust of key advisors.
  • Make the business case for the recommended semantic-layer solution.
  • Contribute to sales and pre-sales efforts.
  • Provide thought leadership on technology trends, new opportunities, innovations, and foreseeable limitations, risks, and concerns.

Desired Qualifications

  • Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
  • Experience with Python, TensorFlow, PyTorch, and tools for building ETL pipelines such as Apache NiFi or Airflow.
  • Practical experience with natural language processing and/or search techniques.
  • Experience with prompt engineering and large language models for enterprise-scale applications.
  • Team lead experience.
  • Ability to collaborate across engineering, research, and product teams across multiple time zones.
  • External client-facing consulting experience.
  • A Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field.
  • Broad experience in diverse machine-learning techniques and agentic systems.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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