Knowledge Engineer / Semantic Expert for AI Sr Manager

Accenture is a leading global professional services company that helps organizations build their digital core and optimize operations. They are seeking a Knowledge Engineer to lead a team in developing scalable AI solutions and Knowledge Graphs, transforming clients' data architecture while collaborating with various stakeholders to achieve project goals.

Responsibilities:

• You lead a team and provide guidance to explore and implement new methodologies, model building techniques, and cutting-edge algorithms, and applying these techniques with the right architecture to solve real-world problems
• You have a deep understanding and ability to remain at the forefront of knowledge engineering, generative AI, LLM, and multi-modal models (with a focus on driving innovation by applying these techniques to new business problems, use cases, and scenarios)
• As needed by the specific problem, you design, evaluate, and maintain ontologies
• As a significant part of this role, you will be justifying the value of innovative generative AI and knowledge graph approaches in the business problems, and you'll be expected to construct methodologies and data architectures that clearly demonstrate their value
• You'll also work collaboratively with teams from both the business and technical side, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project development goals
• Build Knowledge Graph solutions that transform clients’ data architecture
• Design, develop, and implement AI and semantic solutions and ensure that all the pieces work together seamlessly
• Work with the project team, team leaders, project delivery leads, and client stakeholders to create stand-out Data & AI offerings powered by graph-based technologies
• Develop strong relationships with clients and gain the trust of key advisors
• Make the business case for the semantic layer solution recommended to the client
• Pitch in on Accenture sales efforts when needed
• Continue to learn and develop cutting edge Data & AI solutions, especially agentic technologies, provide through leadership on technology trends, new opportunities and innovations, or foreseeable limitations, risks, and concerns

Requirements:

• Bachelor's degree or equivalent (minimum 12 years' work experience). If Associate's Degree, must have equivalent minimum 6-year work experience
• Minimum of 4 years of experience in designing and developing knowledge graph solutions and graph-based machine learning models, functional and technical experience required
• Minimum of 3 end-to-end data pipeline implementation for AI applications, particularly those involving LLMs or similar models, including hands-on design and configuration
• Minimum of 6 years strong knowledge of relational databases, object stores, graph databases (e.g. Stardog, Neo4J, Amazon Neptune), and vector databases
• Minimum of 6 years of experience in Knowledge Graph technologies (e.g. RDF, SPARQL, LPG, SHACL)
• Minimum of 6 years of experience with schema design, ontology management, and Knowledge Graph curation
• Minimum of 6 years of managerial experience working with people with the ability to clearly explain the value of semantic layer and knowledge graphs to senior business and technology stakeholders, and proven track record selling and /or pre-sales and delivering data transformation programs and developing teams
• Experience in Practical experience with NLP techniques and/or Search Techniques, prompt engineering
• Experience with LLMs for enterprise-scale applications
• 5+ years of hands-on experience with cloud platforms (AWS, Azure, GCP)
• 5+ years of experience in Python, with experience in frameworks like Tensorflow, PyTorch, and tools for building ETL pipelines (e.g. Apache NiFi, Airflow)
• 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