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Accenture

Advises businesses and runs their technology

Knowledge Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • At least 7.5 years of experience in Microsoft Azure Data Services.
  • At least 3 years of experience with knowledge graph technologies, including RDF, SPARQL, LPG, and SHACL.
  • At least 3 years of experience in schema design, ontology management, and knowledge graph curation.
  • At least 3 years of experience designing and developing knowledge graph solutions and graph-based machine learning models, both functional and technical.
  • At least 2 years of experience with end-to-end data pipeline implementations for artificial intelligence applications, especially large language models, including hands-on design and configuration.
  • At least 4 years of experience with relational databases, object stores, graph databases such as Stardog, Neo4j, and Amazon Neptune, and vector databases.
  • At least 2 years of experience 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 Google Cloud Platform.
  • At least 2 years of experience with Python and frameworks such as TensorFlow and PyTorch, and tools for building extract, transform, and load pipelines such as Apache NiFi and 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 and external client-facing consulting experience.
  • Strong collaboration skills and ability to work across engineering, research, and product teams in multiple time zones.
  • Proficiency in Microsoft Azure Data Services.
  • Strong expertise in designing and implementing ontologies and semantic models.
  • Experience building and managing knowledge graphs for complex data relationships.
  • Ability to apply advanced analytics techniques to extract insights from structured and unstructured data.
  • Familiarity with data integration and transformation processes within cloud environments.
  • At least 15 years of full-time education.
  • A bachelor's degree or equivalent.

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 these techniques to new business problems, use cases, and scenarios.
  • 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 to 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 program scope.
  • Direct the design, development, and implementation of artificial intelligence and semantic solutions, ensuring the components work together.
  • Work with project leaders, delivery leads, and client stakeholders to develop graph-powered Data and 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, opportunities, innovations, limitations, risks, and concerns.
  • Collaborate with and manage the team to perform, and make team decisions.
  • Engage with multiple teams and contribute to key decisions.
  • Provide solutions to problems for the immediate team and across multiple teams.
  • Lead the development and refinement of knowledge representation models to enhance artificial intelligence capabilities.
  • Facilitate knowledge sharing and communication between cross-functional teams to ensure alignment and integration.
  • Mentor junior team members by providing guidance and support for professional growth.
  • Continuously evaluate emerging technologies and methodologies to improve knowledge engineering processes.

Desired Qualifications

  • Experience with machine learning.
  • A Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or 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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