Data Engineer

Overview

Technical Lead for Context & Ontology, a core engineering team building the enterprise intelligence layer that powers AI agents across domains such as Finance, Legal, Procurement, and HR.

What you'll do

• Lead the architecture, design, and implementation of the enterprise Knowledge Graph (KG) and ontology framework that powers AI-driven enterprise applications.
• Design and maintain scalable knowledge graph schemas, including entity models, relationships, metadata, and business attributes across enterprise domains such as Finance, Legal, Procurement, and Human Resources.
• Own the development and evolution of the ContextLoader and OntologyRegistry services to ensure consistent context management and knowledge retrieval across the platform.
• Provide technical leadership and mentorship to a team of Knowledge Graph Engineers, Ontology Modelers, and Search & Retrieval Engineers.
• Define and govern ontology standards, schema evolution processes, and best practices to ensure consistency and scalability across enterprise applications.
• Design and implement bitemporal versioning strategies for knowledge graph data to support historical tracking, auditing, and future state management.
• Collaborate closely with the Platform Data Engineering team to design robust data ingestion, transformation, and synchronization pipelines.
• Work with business stakeholders and domain experts to translate complex enterprise knowledge into structured semantic models.
• Drive architectural reviews, design discussions, and continuous improvements for graph-based data platforms.
• Ensure high performance, scalability, reliability, and maintainability of the enterprise knowledge platform.

What you'll need

• 12–15 years of experience in software engineering, with significant experience designing enterprise-scale Knowledge Graphs, semantic data models, or ontology-driven platforms.
• Strong expertise in graph data modeling, ontology design principles, and semantic technologies.
• Hands-on experience with graph databases such as Neo4j, Amazon Neptune, TigerGraph, or similar platforms.
• Strong understanding of semantic web standards such as RDF, OWL, SPARQL, or equivalent graph technologies.
• Experience designing enterprise ontologies and collaborating with business domain experts to model complex organizational data.
• Good understanding of vector search, semantic search, retrieval-augmented generation (RAG), and AI-powered information retrieval systems.
• Experience designing scalable data architectures and integrating structured, semi-structured, and unstructured enterprise data sources.
• Strong knowledge of distributed systems, API design, and cloud-native application development.
• Excellent leadership, mentoring, and stakeholder management skills.
• Strong analytical and problem-solving abilities with a passion for building scalable enterprise platforms.
• Minimum 15 years of experience is required.
• 15 years full time education.

Nice to have

• Experience working with AI/ML platforms, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or enterprise AI solutions.
• Exposure to cloud platforms such as Azure, AWS, or Google Cloud.
• Experience building enterprise semantic platforms, metadata management solutions, or large-scale graph-based applications.

Details

• Location: Bangalore (flexible).
• Reporting to: Engineering Manager – Platform Core.