Role Overview :

We are looking for an experienced Technical Lead Knowledge Graph & AI with strong hands-on expertise in Knowledge Graphs, graph data modelling, semantic technologies, AI/ML, and Generative AI.

The role will be responsible for designing and delivering scalable AI-driven solutions that leverage Knowledge Graphs, enterprise data, and modern AI technologies.

Key Responsibilities :

- Lead the technical design, architecture, development, and delivery of Knowledge Graph and AI solutions.
- Design graph data models, ontologies, entities, relationships, taxonomies, and semantic models for enterprise use cases.
- Develop knowledge representation solutions that integrate structured and unstructured enterprise data.
- Design and implement Knowledge Graphs using graph databases and semantic technologies.
- Integrate Knowledge Graphs with AI/ML, Generative AI, LLMs, RAG, and intelligent applications.
- Build data pipelines for ingestion, transformation, enrichment, entity resolution, and integration of structured and unstructured data.
- Design APIs, data services, and integration patterns to make graph and AI capabilities available to enterprise applications.
- Develop and optimize graph queries and semantic retrieval solutions.
- Work with graph technologies such as Neo4j, RDF, SPARQL, or equivalent platforms.
- Collaborate with Data Engineers, AI Engineers, Architects, Product teams, and business stakeholders to translate requirements into scalable technical solutions.
- Lead technical design discussions, architecture reviews, code reviews, and solution design workshops.
- Define reusable engineering patterns and standards for graph modelling, semantic data, AI integration, security, scalability, and performance.
- Troubleshoot complex data, graph, application,



and AI integration issues and drive root-cause resolution.
- Evaluate technology options and make recommendations for graph platforms, semantic technologies, AI frameworks, and enterprise data architectures.
- Ensure solutions meet requirements for performance, scalability, reliability, security, data quality, and maintainability.
- Mentor engineers and provide technical guidance on Knowledge Graph, AI, and up-to-date data technologies.
- Drive continuous improvement across Knowledge Graph and AI platforms and engineering practices.

Required Skills & Experience :

- 9 - 14 years of experience in software engineering, data engineering, AI/ML engineering, solution architecture, or related technology roles.
- Strong hands-on experience with Knowledge Graphs and graph data modelling.
- Strong understanding of entities, relationships, ontologies, semantic modelling, taxonomies, and knowledge representation.
- Hands-on experience with Neo4j, RDF, SPARQL, or equivalent graph technologies.
- Strong programming skills in Python or equivalent.
- Experience with data integration, ETL/ELT, APIs, and data pipelines.
- Good understanding of AI, Machine Learning, Generative AI, and LLM architectures.
- Experience integrating Knowledge Graphs with AI/LLM-based applications and enterprise data.
- Strong understanding of graph querying, data modelling, semantic retrieval, and graph-based solution design.
- Experience with software architecture, design patterns, distributed systems, scalability, and performance optimization.
- Strong technical leadership experience, including architecture/design reviews, code reviews, mentoring, and technical decision-making.
- Strong analytical, troubleshooting, communication, and stakeholder-management skills.
- Ability to work independently on complex technical problems and drive solutions from architecture through production.

📌 Virtusa - Technical Lead - Knowledge Graph & AI (India)
🏢 Virtusa Consulting Services
📍 India