Project Role : Knowledge Engineer

Project Role Description : 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.

Must have skills : Microsoft Azure Data Services

Good to have skills : Graph Databases, Data Engineering

Minimum 12 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Summary:

AI Powered Tech Talent

You lead a significant knowledge engineering scope and function within a large program actively contribute to thought leadership. You shape how a substantial body of work formulates real-world problems into scalable AI and KG solutions, and set the technical direction for that scope. You lead a team and guide exploration and implementation of new methodologies, model building techniques, and cutting-edge algorithms. You remain at the forefront and drive innovation by applying these techniques to new business problems, use cases, and scenarios. You design, evaluate, and maintain ontologies, and establish the standards others follow. You justify the value to business and technology stakeholders, and construct the methodologies and data architectures that demonstrate it. You publish or present perspective beyond the immediate project. You work across business and technical teams to drive end-to-end delivery for their scope.

Leads the build of Knowledge Graph solutions that transform a client's data architecture within program scope.

Directs the design, development, and implementation of AI and semantic solutions, ensuring all the pieces work together seamlessly.

Works with project leaders, delivery leads, and client stakeholders to create stand-out, graph-powered Data & AI offerings.

Develops strong client relationships and earns the trust of key advisors.

Makes the business case for the semantic layer solution recommended to the client.

Contributes meaningfully to Accenture sales and pre-sales efforts.

Provides thought leadership on technology trends, new opportunities, innovations, and foreseeable limitations, risks, and concerns.

Bachelor's degree or equivalent

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.

You 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 experience

Ph.D. in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.

Broad experience in diverse ML techniques and agentic systems.

As a Knowledge Engineer, a typical day involves designing and structuring comprehensive knowledge frameworks that empower artificial intelligence systems to reason effectively and make well-informed decisions. This role requires capturing expert knowledge and transforming unstructured information into ontologies, knowledge graphs, and semantic models. Throughout the day, the Knowledge Engineer ensures that these knowledge representations maintain accuracy and contextual relevance to support automation and generate valuable insights. Additionally, the role includes applying advanced analytical techniques to knowledge graphs to facilitate problem-solving and derive actionable intelligence that benefits various organizational functions.

Roles & Responsibilities:

Expected to be an SME, collaborate and manage the team to perform.
Responsible for team decisions.
Engage with multiple teams and contribute on key decisions.
Expected to provide solutions to problems that apply across multiple teams.
Lead the development and refinement of knowledge models to enhance artificial intelligence capabilities.
Facilitate communication and coordination among cross-functional teams to ensure alignment on knowledge engineering objectives.
Mentor junior team members by providing guidance and support in knowledge representation and analytics techniques.

Professional & Technical Skills:

Must To Have Skills: Proficiency in Microsoft Azure Data Services.
Good To Have Skills: Data Engineering, Graph Databases.
Experience in designing and implementing ontologies and semantic models to represent complex knowledge domains.
Strong analytical skills to apply advanced techniques on knowledge graphs for deriving insights.
Familiarity with data integration and transformation processes within cloud-based environments.
Ability to work with large-scale data sets and ensure data quality and contextual accuracy in knowledge frameworks.

Additional Information:

The candidate should have minimum 12 years of experience in Microsoft Azure Data Services.
This position is based at our Chennai office.
A 15 years full time education is required.