Knowledge Engineer / Semantic Expert for AI

Knowledge EngineerAs a Knowledge Engineer, you formulate real-world problems into practical, efficient, and scalable AI and Knowledge Graph problems.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.The Work: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 seamlesslyWork with the project team, team leaders, project delivery leads, and client stakeholders to create stand-out Data & AI offerings powered by graph-based technologiesDevelop strong relationships with clients and gain the trust of key advisorsMake the business case for the semantic layer solution recommended to the clientPitch in on Accenture sales efforts when neededContinue 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.Travel may be required for this role. The amount of travel will vary from 0% to 100% depending on business need and client requirements.Here's what you need:Bachelor's degree or equivalent (minimum 12 years' work experience). If Associate's Degree, must have equivalent minimum 6-year work experienceMinimum of 2 or more of the below Requirements:Minimum of 2 years of experience in Knowledge Graph technologies (e.g. RDF, SPARQL, LPG, SHACL)Minimum of 2 years of experience with schema design, ontology management, and Knowledge Graph of 2 years of experience in designing and developing knowledge graph solutions and graph-based machine learning models, functional and technical experience required.Minimum of 1 end-to-end data pipeline implementation for AI applications, particularly those involving LLMs or similar models, including hands-on design and configurationMinimum of 2 year and strong knowledge of relational databases, object stores, graph databases (e.g. Stardog, Neo4J, Amazon Neptune), and vector databasesBonus Points If:2+ years of hands-on experience with cloud platforms (AWS, Azure, GCP)2+ years of 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 techniquesPrompt engineering, and LLMs for enterprise-scale 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 experiencePh.D. in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.Broad experience in diverse ML techniques and agentic systems.