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Accenture

Advises businesses and runs their technology

Knowledge Engineer

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeChennai, Tamil Nadu, IndiaNo salary listed

About the Job

Requirements

  • A bachelor's degree or equivalent is required.
  • A minimum of 12 years of experience in Microsoft Azure Data Services is required.
  • At least four of the listed experience qualifications are required: 3 years with knowledge graph technologies (RDF, SPARQL, LPG, SHACL); 3 years in schema design, ontology management, and knowledge graph curation; 3 years designing and developing knowledge graph solutions and graph-based machine learning models; 2 years implementing end-to-end data pipelines for artificial intelligence applications, especially large language models; 4 years working with relational databases, object stores, graph databases, and vector databases; 2 years leading a team or workstream within a larger program.
  • At least 2 years of hands-on experience with cloud platforms such as AWS, Azure, or GCP is required.
  • At least 2 years of Python experience, including familiarity with TensorFlow, PyTorch, and tools for building extract, transform, and load pipelines such as Apache NiFi or Airflow, is required.
  • Practical experience with natural language processing or search techniques is required.
  • Experience with prompt engineering and large language models for enterprise-scale applications is required.
  • Experience leading a team is required.
  • External client-facing consulting experience is required.
  • A Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field is required.
  • Broad experience with diverse machine learning techniques and agentic systems is required.
  • Proficiency in Microsoft Azure Data Services is required.
  • Experience designing and implementing ontologies and semantic models to represent complex knowledge domains is required.
  • Strong analytical ability to apply advanced techniques to knowledge graphs to derive insights is required.
  • Familiarity with data integration and transformation processes in cloud-based environments is required.
  • Ability to work with large-scale datasets and ensure data quality and contextual accuracy in knowledge frameworks is required.

Responsibilities

  • Design and structure knowledge frameworks that enable artificial intelligence systems to reason and make informed decisions.
  • Capture and translate expert and unstructured knowledge into ontologies, knowledge graphs, and semantic models, ensuring accuracy and context for automation and insights.
  • Apply advanced analytics to knowledge graphs to drive problem-solving and actionable insights.
  • 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 artificial intelligence 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.
  • Explain the value to business and technology stakeholders and construct methodologies and data architectures to demonstrate it.
  • 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 program scope.
  • Direct the design, development, and implementation of artificial intelligence and semantic solutions.
  • Work with project leaders, delivery leads, and client stakeholders to develop graph-powered data and artificial intelligence offerings.
  • Develop client relationships and earn the trust of key advisors.
  • Make the business case for the semantic-layer solution recommended to the client.
  • Contribute to sales and pre-sales efforts.
  • Provide thought leadership on technology trends, new opportunities, innovations, foreseeable limitations, risks, and concerns.
  • Collaborate with and manage the team to perform.
  • Make team decisions.
  • Engage with multiple teams and contribute to key decisions.
  • Provide solutions to problems that apply across multiple teams.
  • Lead development and refinement of knowledge models to enhance artificial intelligence capabilities.
  • Facilitate communication and coordination among cross-functional teams to align on knowledge engineering objectives.
  • Mentor junior team members by providing guidance and support in knowledge representation and analytics techniques.
  • Design and structure knowledge frameworks and transform unstructured information into ontologies, knowledge graphs, and semantic models, maintaining accuracy and contextual relevance for automation and insights.

Desired Qualifications

  • Data engineering experience is desirable.
  • Graph database experience is desirable.

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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