Knowledge Engineer

Overview

Knowledge Engineer role designing and structuring knowledge frameworks, ontologies, knowledge graphs and semantic models that enable AI systems to reason and make informed decisions.

What you'll do

• Design and structure knowledge frameworks that enable AI systems to reason and make informed decisions.
• Capture and translate expert and unstructured knowledge into ontologies, knowledge graphs, and semantic models, ensuring accuracy and context for automation and insights.
• Apply advanced analytics on knowledge graphs to drive problem-solving and actionable insights.
• Lead the build of Knowledge Graph solutions that transform a client's data architecture within program scope.
• Direct the design, development, and implementation of AI and semantic solutions, ensuring all the pieces work together seamlessly.
• Work with project leaders, delivery leads, and client stakeholders to create graph-powered Data & AI offerings.
• Develop strong client relationships and earn the trust of key advisors.
• Make the business case for the semantic layer solution recommended to the client.
• Contribute to Accenture sales and pre-sales efforts.
• Provide thought leadership on technology trends, new opportunities, innovations, and foreseeable limitations, risks, and concerns.
• Lead efforts to maintain the quality and consistency of knowledge representations within the team.
• Facilitate knowledge sharing and continuous learning among team members.
• Support junior professionals by guiding their development and assisting with complex challenges.

What you'll need

• Bachelor's degree or equivalent, plus at least 4 of the following: minimum 3 years of experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL); minimum 3 years of experience in schema design, ontology management, and KG curation; minimum 3 years of designing and developing KG solutions and graph-based ML models (functional + technical); minimum 2 years of experience with end-to-end data pipeline implementations for AI applications (esp. LLMs), with hands-on design and configuration; minimum 4 years of experience with strong knowledge of relational databases, object stores, graph databases (Stardog, Neo4J, Amazon Neptune), and vector databases; minimum 2 years of experience in leading a team or workstream within a larger program; 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 techniques; prompt engineering, and LLMs for enterprise-scale applications; team lead experience; strong collaboration skills with the ability to work across engineering, research, and product teams across multiple time zones; external client-facing consulting experience.
• Must have: Microsoft Azure Data Services.
• Minimum 5 years of experience is required.
• 15 years full time education.

Nice to have

• Experience with Graph Databases and Data Engineering.
• Ph.D. in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.
• Broad experience in diverse ML techniques and agentic systems.

Details

• Based at the Bengaluru office.