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Accenture

Advises businesses and runs their technology

AI Knowledge Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Information Systems, or another relevant discipline is required.
  • At least 4 years of relevant experience in Data/AI, data engineering, software engineering, or related areas, with recent hands-on exposure to Knowledge Graphs, semantic technologies, or Knowledge Engineering.
  • Strong understanding of knowledge representation and semantic modeling, including entities, relationships, ontologies, taxonomies, and semantic models.
  • Hands-on experience with knowledge graphs or graph databases and associated query/modeling approaches such as RDF/SPARQL or property graphs/Cypher.
  • Strong programming skills in Python, with experience integrating APIs and processing structured and unstructured information.
  • Understanding of Generative AI and LLM architectures, including embeddings, vector search, semantic search, and Retrieval-Augmented Generation (RAG).
  • Experience with information retrieval, document processing, or NLP, including techniques such as entity extraction, classification, or entity resolution.
  • Understanding of how semantic layers, metadata, and enterprise knowledge can provide trusted business context to AI applications.
  • Familiarity with software engineering practices including Git, testing, CI/CD, APIs, and containerization.
  • Ability to translate business concepts into technical knowledge models and work effectively in multidisciplinary environments.

Responsibilities

  • Design and maintain enterprise knowledge models, semantic layers, ontologies, taxonomies, and knowledge graphs that represent business concepts, entities, and relationships.
  • Transform structured and unstructured enterprise information into trusted, reusable, and AI-ready knowledge by applying appropriate metadata, semantics, and relationships.
  • Design and implement enterprise search, document retrieval, and RAG solutions, combining semantic, vector, keyword, and graph-based retrieval where appropriate.
  • Develop knowledge ingestion and enrichment capabilities, including entity and relationship extraction, classification, linking, and entity resolution, using NLP and LLM techniques.
  • Contribute to agent context engineering, ensuring AI agents receive relevant enterprise knowledge, metadata, instructions, and contextual information to support reliable responses and actions.
  • Support the design of appropriately scoped agent memory, enabling agents to retain and reuse relevant context while considering privacy, security, provenance, and lifecycle requirements.
  • Integrate knowledge solutions with enterprise data platforms, document repositories, metadata/catalog platforms, APIs, and AI applications.
  • Apply knowledge quality, provenance, lineage, access control, and governance principles to improve the trustworthiness and traceability of knowledge used by AI solutions.
  • Apply software engineering best practices to develop scalable, maintainable, testable, and production-ready solutions.
  • Collaborate with AI engineers, data engineers, architects, domain experts, and business stakeholders to translate business knowledge into effective technical solutions.

Desired Qualifications

  • A master's degree or PhD is considered an advantage.
  • Experience designing or implementing GraphRAG or hybrid retrieval solutions.
  • Experience with agentic AI, including context engineering, agent memory patterns, or multi-agent solutions.
  • Experience with enterprise metadata/catalog platforms such as Alation, Collibra, Microsoft Purview, Informatica, or equivalent technologies.
  • Experience integrating knowledge graphs with Databricks, Snowflake, cloud data platforms, lakehouses, or data warehouses.
  • Familiarity with MCP and developing REST APIs.
  • Relevant cloud, data, graph, or AI certifications.

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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