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Accenture

Advises businesses and runs their technology

Knowledge Engineering Senior Manager

Engineering LeadershipPosted on Nov 13
Full-timeHybrid

About the Job

Requirements

  • At least 6 years of experience with knowledge graph and semantic technologies, including RDF, SPARQL, LPG, and SHACL, as part of 10 or more years in data, artificial intelligence, search, or information architecture.
  • At least 6 years of experience in schema design, ontology management, and knowledge graph curation.
  • At least 4 years of functional and technical experience designing and developing knowledge graph solutions and graph-based machine learning models.
  • At least 3 years of experience implementing end-to-end data pipelines for artificial intelligence applications, especially large language models, including hands-on design and configuration.
  • At least 6 years of experience with relational databases, object stores, graph databases such as Stardog, Neo4j, and Amazon Neptune, and vector databases.
  • At least 5 years of experience leading knowledge, data, or artificial intelligence transformation in customer service, contact center, or customer experience, with working knowledge of service metrics such as containment, first-contact resolution, average handle time, customer satisfaction, and cost-to-serve, and how knowledge quality affects them.
  • At least 6 years of managerial experience leading people, ability to explain the value of semantic layers and knowledge graphs to senior business and technology stakeholders, a proven track record in sales and/or pre-sales, experience delivering data transformation programs, and experience developing teams.
  • A bachelor's degree or equivalent experience of 12 years.
  • External thought leadership experience, such as publishing points of view, speaking at events, or representing the practice in the broader artificial intelligence community.

Responsibilities

  • Oversee knowledge engineering across multiple programs, providing technical direction and quality oversight while maintaining accountability for delivery health, team performance, and measurable outcomes such as answer accuracy, first-contact resolution, handle time, and knowledge reuse.
  • Inspire and challenge teams' designs, unblock delivery when it stalls, and give clients a candid view of what it takes to get artificial intelligence into production.
  • Own the strategy and architecture for a single source of truth for service knowledge, consolidating knowledge bases, documents, product and policy data, and case history into a governed knowledge graph and semantic layer.
  • Set standards for how service ontologies and taxonomies are designed, evaluated, and maintained across programs.
  • Define how knowledge grounds virtual agents, agent-assist copilots, and analytics agents in partnership with artificial intelligence solution engineering and enterprise artificial intelligence architecture leaders.
  • Establish knowledge governance and operating models with clients, including ownership, review cycles, content lifecycle, access rules, and feedback loops that turn knowledge gaps found in service interactions into new content.
  • Shape knowledge around how customers and service agents look for answers, translating customer experience journeys and conversation designs into supporting knowledge structures.
  • Lead sales and pre-sales efforts, shaping service knowledge and data transformation programs that turn one project into a lasting partnership.
  • Make and defend the business case for semantic layer and knowledge graph solutions at the executive level, connecting knowledge quality to service outcomes and cost-to-serve.
  • Develop trusted-advisor relationships with senior client stakeholders, including service, customer experience, and knowledge management leaders.
  • Drive thought leadership on knowledge as the foundation for artificial intelligence in customer service, positioning Song as a credible industry voice.
  • Lead, coach, and grow teams of knowledge engineers, developing their technical depth, leadership skills, and client acumen so they can become workstream and program owners.
  • Build inclusive, high-performing teams where practitioners are supported, challenged, and able to grow into stronger leaders.
  • Lead creation of reusable assets that advance the discipline beyond a single engagement, such as service ontologies, knowledge models, curation pipelines, and accelerators.
  • Bring artificial-intelligence-augmented delivery into teams, applying artificial intelligence tooling across story grooming, solutioning, testing and triage, and development to raise speed and quality.

Desired Qualifications

  • Experience with service knowledge management platforms such as Salesforce Knowledge, ServiceNow Knowledge Management, eGain, or Zendesk.
  • Experience establishing Knowledge-Centered Service or similar knowledge management practices at enterprise scale.
  • Experience with GraphRAG or other knowledge-grounded retrieval for artificial intelligence agents.
  • Practical experience with natural language processing and/or search techniques, prompt engineering, and large language models for enterprise-scale applications.
  • At least 5 years of hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud.
  • At least 5 years of experience with Python, frameworks such as TensorFlow or PyTorch, and tools for building extract, transform, load pipelines such as Apache NiFi or Airflow.
  • Broad experience in diverse machine learning techniques and agentic systems.
  • External client-facing consulting experience.
  • A Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field.

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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