[Hiring] Knowledge Engineer / Semantic Expert for AI Sr Manager @Accenture

Role Description

As 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, applying these techniques with the right architecture to solve real-world problems.

• Deep understanding of knowledge engineering, generative AI, LLM, and multi-modal models.
• Design, evaluate, and maintain ontologies as needed.
• Justify the value of innovative generative AI and knowledge graph approaches in business problems.
• Construct methodologies and data architectures that demonstrate their value.
• Collaborate with teams from both the business and technical side, including users, use case representatives, business owners, engineers, architects, and UI designers.

Qualifications

• 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.
• Minimum of 3 end-to-end data pipeline implementations for AI applications, particularly those involving LLMs or similar models.
• 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 with the ability to explain the value of semantic layer and knowledge graphs to senior stakeholders.
• Proven track record in selling and/or pre-sales and delivering data transformation programs and developing teams.

Requirements

• Experience in practical 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.
• 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.

Benefits

• Market competitive suite of benefits including medical, dental, vision, life, and long-term disability coverage.
• 401(k) plan.
• Bonus opportunities.
• Paid holidays and paid time off.