Knowledge Engineering Associate Director

Accenture•Miami, FL

2d•$138,800 - $434,000

About The Position

As an Associate Director, the role owns Accenture’s enterprise knowledge engineering services and technical discipline. This includes developing and approving scaled ontology-creation methods, semantic-layer design, and knowledge-agent patterns, including the boundary between enterprise ontology work and problem-scoped ontology work. The role also owns the related asset portfolio, such as ontology templates, entity-resolution patterns, and semantic-serving reference architectures. The Associate Director develops and communicates the technical point of view on enterprise knowledge engineering, explaining the value of semantic layers to executive stakeholders and defending technical decisions to architects. The role may require travel, varying from 0% to 100% depending on business need 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 such as RDF, SPARQL, SHACL, and property graphs, and enterprise graph databases.
At least 6 years of managerial or discipline-leadership experience, including 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, with a minimum of 12 years of work experience; candidates with an Associate's degree must have at least 6 years of work experience.
Demonstrated ability to establish credibility with client executives through technical depth.
A clear, defensible point of view on the current AI frontier and the ability to articulate it publicly.

Nice To Haves

Retrieval-augmented generation and agent context engineering at enterprise scale.
Experience running ontology governance, including versioning meaning like engineers version code.
Experience with multi-tenant or federated semantic-layer architectures.
Comfort being outranked on pipeline conversations and outvoting on technical ones.
A track record of editing methodology like engineers edit code.
Relationships with frontier partners such as Anthropic, OpenAI, hyperscaler AI organizations, or equivalent.

Responsibilities

Own, defend, evolve, and approve the methodology for scaled ontology creation, semantic-layer design, and knowledge-agent patterns.
Define and maintain the boundary between enterprise ontology work and problem-scoped ontology work.
Own the knowledge engineering asset portfolio, including ontology templates, entity-resolution patterns, and semantic-serving reference architectures.
Develop and communicate the technical point of view on semantic layers and engineered meaning for AI.
Explain the value of the semantic layer to senior business stakeholders and defend technical modeling decisions to architects.
Publish or speak publicly about the discipline and its technical perspective.