Knowledge Engineer

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
15 year(s) of experience is required


Educational Qualification : 15 years full time education


Summary:

AI Powered Tech Talent

You lead the complete knowledge engineering scope on our most strategic and complex programs lead creation of thought leadership, innovation, and assets for the discipline. You own how the most demanding programs formulate real-world problems into scalable AI and KG solutions, setting strategy and architecture end to end. You lead and develop teams of engineers, building capability across the discipline and guiding adoption of new methods and algorithms. You define what staying at the forefront means for the practice drive innovation and translate it into new offerings. You set the standards for how ontologies are designed, evaluated, and maintained across programs. You make the case to senior stakeholders and shape the methodologies and data architectures that prove value at scale. You lead the creation of thought leadership, innovation, and reusable assets that advance the discipline beyond any single engagement. You partner with business and technical leaders to direct end-to-end delivery across complex, multi-stakeholder programs.
Lead the complete Knowledge Graph solution scope that transforms data architecture for our most strategic and complex clients.
Own the design, development, and implementation of AI and semantic solutions across the program.
Partner with project leaders, delivery leads, and senior client stakeholders to create stand-out, graph-powered offerings.
Develop trusted-advisor relationships with senior client stakeholders.
Make and defend the business case for the semantic layer solution at the executive level.
Lead Accenture sales and pre-sales efforts and shape data transformation programs.
Drive the practice''s thought leadership, innovation, and asset development on trends and agentic technologies, and develop the teams who deliver them.
Bachelor''s degree or equivalent
Bachelor''s degree or equivalent, plus all of the following:
Minimum 6 years of experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL)
Minimum 6 years of experience in schema design, ontology management, and KG curation
Minimum 4 years designing and developing KG solutions and graph-based ML models (functional + technical)
Minimum 3 years of experience with end-to-end data pipeline implementations for AI applications (esp. LLMs), with hands-on design and configuration
Minimum 6 years of experience with strong knowledge of relational databases, object stores, graph databases (Stardog, Neo4J, Amazon Neptune), and vector databases
Minimum 6 years of managerial experience leading people, able to explain the value of the semantic layer and knowledge graphs to senior business and technology stakeholders, with a proven track record in sales and/or pre-sales and in delivering data transformation programs and developing teams
Experience in Practical experience with 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.
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 organizing comprehensive knowledge frameworks that empower artificial intelligence systems to perform reasoning and make well-informed decisions. This role requires capturing expert knowledge and transforming unstructured information into structured ontologies, knowledge graphs, and semantic models. Throughout the day, the Knowledge Engineer ensures that these models maintain accuracy and contextual relevance to support automation and generate meaningful insights. Additionally, the role includes applying advanced analytical techniques to knowledge graphs to facilitate effective problem-solving and deliver actionable intelligence across various domains.

Roles Responsibilities:

Expected to be a SME with deep knowledge and experience.

Should have Influencing and Advisory skills.

Responsible for team decisions.

Engage with multiple teams and contribute on key decisions.

Expected to provide solutions to problems that apply across multiple teams.

Collaborate with stakeholders to align knowledge frameworks with organizational goals and evolving technological landscapes.

Mentor and guide junior team members to foster skill development and knowledge sharing within the team.

Professional Technical Skills:


Must To Have Skills:

Proficiency in Microsoft Azure Data Services.

Good To Have Skills: Experience with Graph Databases, Data Engineering.

Strong understanding of knowledge representation techniques including ontologies and semantic modeling.

Experience in designing and managing knowledge graphs to support artificial intelligence applications.

Ability to apply advanced analytics and reasoning methods on complex data structures.

Familiarity with data integration and transformation processes to ensure data quality and consistency.

The candidate should have minimum 15 years of experience in Microsoft Azure Data Services.

This position is based at our Chennai office.

A 15 years full time education is required.


Qualification 15 years full time education