Key Skills

Job Description

YOU ARE You lead a significant knowledge engineering scope and function within a large program; actively contribute to thought leadership. You shape how a substantial body of work formulates real-world problems into scalable AI and KG solutions, and set the technical direction for that scope. You lead a team and guide exploration and implementation of new methodologies, model building techniques, and cutting-edge algorithms. You remain at the forefront and drive innovation by applying these techniques to new business problems, use cases, and scenarios. You design, evaluate, and maintain ontologies, and establish the standards others follow. You justify the value to business and technology stakeholders, and construct the methodologies and data architectures that demonstrate it. You publish or present perspective beyond the immediate project. You work across business and technical teams to drive end-to-end delivery for their scope. THE WORK Leads the build of Knowledge Graph solutions that transform a client's data architecture within program scope. Directs the design, development, and implementation of AI and semantic solutions, ensuring all the pieces work together seamlessly Works with project leaders, delivery leads, and client stakeholders to create stand-out, graph-powered Data & AI offerings Develops strong client relationships and earns the trust of key advisors Makes the business case for the semantic layer solution recommended to the client. Contributes meaningfully to Accenture sales and pre-sales efforts. Provides thought leadership on technology trends, new opportunities, innovations, and foreseeable limitations, risks, and concerns. EDUCATION Bachelor's degree or equivalent Basic (required) Qualification Bachelor's degree or equivalent, plus at least 4 of the following: Professional experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, KG curation Proven experience designing and developing KG solutions and graph-based ML models (functional + technical) Familiarity end-to-end data pipeline implementations for AI applications (esp. LLMs), with hands-on design and configuration Strong knowledge & practical experience of relational databases, object stores, graph databases (Stardog, Neo4J, Amazon Neptune), and vector databases Experience in leading a team or workstream within a larger program Preferred Qualification Hands-on experience with cloud platforms (AWS, Azure, GCP) Experience in Python, with experience in frameworks like Tensorflow, PyTorch, and tools for building ETL pipelines (e.g. Apache NiFi, Airflow) Practical experience with NLP and/or Search techniques Prompt engineering, and LLMs for enterprise-scale applications. You have team lead experience Strong collaboration skills with the ability to work across engineering, research, and product teams across multiple time zones. You have external client-facing consulting experience Ph.D. in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field. Broad experience in diverse ML techniques and agentic systems.

Core Responsibilities

Lead the design and delivery of Knowledge Graph, AI, and semantic solutions, including ontology standards and graph-powered data architectures. Guide a team, build client relationships, make the business case for recommended solutions, and contribute to thought leadership and sales efforts.

Requirements

A bachelor's degree or equivalent is required, along with at least four listed qualifications, including Knowledge Graph technologies, ontology or schema management, KG solution development, AI data pipelines, database experience, or team leadership. Preferred qualifications include cloud platforms, Python and ML frameworks, NLP or search, prompt engineering and LLMs, client-facing consulting, and a relevant PhD.