Virtusa - Technical Lead - Knowledge Graph & AI

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 modern 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.