Knowledge Engineer / Semantic Expert for AI

Job title: Knowledge Engineer / Semantic Expert for AI

About the Role Accenture is helping companies use generative AI and semantic layers to reinvent their enterprise and optimize business functions for breakthrough innovation and competitive advantage. As a Knowledge Engineer, you will translate real-world problems into scalable AI and Knowledge Graph solutions, lead teams, and apply cutting-edge algorithms and architectures to deliver end-to-end data & AI projects.

What You'll Do

• Build Knowledge Graph solutions that transform clients’ data architecture.
• Design, develop, and implement AI and semantic solutions and ensure all components work together seamlessly.
• Work with project teams, leaders, delivery leads, and client stakeholders to create standout Data & AI offerings powered by graph-based technologies.
• Develop strong relationships with clients and gain trust of key advisors.
• Make the business case for the semantic layer solution and demonstrate value to clients.
• Contribute to Accenture sales efforts when needed.
• Continue learning and developing cutting-edge Data & AI solutions, providing leadership on technology trends, opportunities, and potential risks.
• Travel may be required; travel amount varies from 0% to 100% depending on business needs.

What We're Looking For

• Bachelor's degree or equivalent (minimum 12 years' work experience). If Associate’s Degree, minimum 6 years' experience.
• Minimum 4 years designing and developing knowledge graph solutions and graph-based ML models.
• Minimum 3 end-to-end data pipeline implementations for AI applications, especially those involving LLMs.
• Minimum 6 years of strong knowledge of relational databases, object stores, graph databases (e.g., Stardog, Neo4J, Amazon Neptune), and vector databases.
• Minimum 6 years of experience with Knowledge Graph technologies (e.g., RDF, SPARQL, LPG, SHACL).
• Minimum 6 years of experience with schema design, ontology management, and Knowledge Graph curation.
• Minimum 6 years of managerial experience with the ability to explain the value of semantic layers and knowledge graphs to senior stakeholders, plus a track record in selling/pre-sales and delivering data transformation programs.
• Bonus Points: Practical NLP or search techniques, prompt engineering; experience with enterprise-scale LLMs; 5+ years cloud (AWS, Azure, GCP); 5+ years Python with frameworks like TensorFlow, PyTorch, and ETL tools (e.g., NiFi, Airflow); strong collaboration across time zones; external client-facing consulting experience; Ph.D. in CS, EE, Math, or related field; broad ML techniques and agentic systems.

Nice to Have

• Practical experience with NLP techniques and/or Search Techniques, prompt engineering
• Experience with LLMs for enterprise-scale applications
• 5+ years hands-on experience with cloud platforms (AWS, Azure, GCP)
• 5+ years of Python experience with frameworks like TensorFlow, PyTorch, and ETL tools (e.g., Apache NiFi, Airflow)
• Strong collaboration skills across engineering, research, and product teams across multiple time zones
• External client-facing consulting experience
• Ph.D. in Computer Science, Electrical Engineering, Mathematics, or related field
• Broad experience in diverse ML techniques and agentic systems

Compensation & Benefits

• Compensation varies by location; role location ranges provided in the posting (USD) with examples such as California $132,500 to $338,300; Cleveland $122,700 to $270,600; Colorado $132,500 to $292,200; District of Columbia $141,100 to $311,200; Illinois $122,700 to $292,200; Maine $112,900 to $249,000; Maryland $132,500 to $292,200; Massachusetts $132,500 to $311,200; Minnesota $132,500 to $292,200; New York $122,700 to $338,300; New Jersey $141,100 to $338,300; Virginia $122,700 to $311,200; Washington $141,100 to $311,200.
• Benefits include medical, dental, vision, life, and long-term disability coverage; a 401(k) plan; bonus opportunities; paid holidays; and paid time off.