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.