Knowledge Engineering Associate Director

Accenture•Chicago, IL

About The Position

As an Associate Director, the role is the technical owner of Accenture’s enterprise knowledge engineering services within the Digital Core Reinvention practice. The position owns and evolves the methodology for scaled ontology creation, semantic-layer design, and knowledge-agent patterns, including defining the boundary between enterprise ontology work and problem-scoped ontology work. It also owns the portfolio of assets used in engagements, such as ontology templates, entity-resolution patterns, and semantic-serving reference architectures. The role establishes and communicates Accenture’s technical point of view on semantic layers and engineered meaning for AI, addressing both executive business audiences and technical architects. Travel may be required and can range from 0% to 100%, depending on business needs and client requirements.

Requirements

At least 10 years of experience in knowledge engineering, semantic web, ontology design, or adjacent data disciplines, including at least 2 years specifically on AI/LLM-based work.
At least 6 years of experience with knowledge-graph technologies, including RDF, SPARQL, SHACL, property graphs, and enterprise graph databases.
At least 6 years of managerial or discipline-leadership experience, including the ability to explain the value of the semantic layer to senior stakeholders.
At least 2 years of publishing or speaking publicly in the discipline.
At least 3 years owning a productized offering, platform, or methodology, rather than only consulting within one.
Bachelor’s degree or equivalent, or a minimum of 12 years of work experience. Applicants with an associate’s degree must have at least 6 years of work experience.
Demonstrated ability to earn the confidence of client executives through technical depth.
A clear, defensible point of view on the current AI frontier and the ability to articulate it publicly.
Applicants for US employment must have work authorization that does not now or in the future require visa sponsorship.

Nice To Haves

Experience with retrieval-augmented generation and agent context engineering at enterprise scale.
Experience running ontology governance, including versioning meaning in a manner comparable to versioning code.
Experience with multi-tenant or federated semantic-layer architectures.
Comfort deferring to others on pipeline conversations while asserting a technical point of view in technical decisions.
A track record of editing methodology in an engineering-like, iterative manner.
Relationships with frontier partners such as Anthropic, OpenAI, hyperscaler AI organizations, or equivalents.

Responsibilities

Own, defend, evolve, and approve the methodology for scaled ontology creation, semantic-layer design, and knowledge-agent patterns.
Define the boundary between enterprise knowledge engineering and problem-scoped ontology work.
Own the technical asset portfolio, including ontology templates, entity-resolution patterns, and semantic-serving reference architectures.
Develop and communicate a technical point of view on the value of semantic layers and engineered meaning for AI to executives, technical audiences, and the broader market.
Represent and explain technical modeling decisions, including OWL decisions, to client and technical stakeholders.