
Core Engineering, Knowledge Graph Software Engineer, Associate/ Vice President, Singapore
- Singapore
- Permanent
- Full-time
- Design, develop and maintain robust data retrieval systems to supply our Generative AI infrastructure with the organizational and systems knowledge they need from vast unstructured data corpuses.
- Lead the modeling and evolution of the knowledge graph, ensuring efficient, scalable, and accurate representation of complex unstructured information across the organization.
- Ensure conformance with the firms security and AI standards.
- Integrate our generative AI systems with the knowledge graph to enhance AI-driven reasoning, semantic search, and contextual data retrieval, ensuring accuracy and reducing hallucinations.
- Work extensively with the vendor products, configuring integrations with various internal data sources and leveraging capabilities to build a unified and intelligent enterprise data retrieval.
- Collaborate closely with product managers, AI/ML engineers, and other stakeholders to understand data requirements, define KPIs, and deliver data solutions that align with business objectives.
- Ensure data quality, integrity, and security within the knowledge graph, implementing robust validation and monitoring mechanisms.
- Contribute to the continuous improvement of data engineering best practices, tools, and processes within the SDLC Engineering team.
- Bachelor's or Master's degree in Computer Science, Data Engineering, or a related technical field.
- Minimum 5 (for associate)/ 10 (for vice president) years of hands-on experience in data engineering, with a strong focus on building scalable distributed systems.
- Proficiency in programming languages such as Python or Java.
- In depth knowledge of modern network stacks, ideally with http proxies / gateways / load-balancing.
- Experience with cloud platforms (e.g., AWS, GCP, Azure).
- Solid understanding of data structures, algorithms.
- Familiarity with SDLC processes and tools.
- Familiarity with Large Language Models (LLMs) and their application in enterprise search or knowledge management.
- Familiarity with LLM communication protocols (MCP, A2A etc).
- Direct experience with enterprise AI search platforms that leverage knowledge graphs.
- Proven track record in designing and implementing production-grade knowledge graphs.
- Experience with Retrieval Augmented Generation (RAG) methodologies and prompt engineering for LLMs.
- Experience with data governance, metadata management, and data cataloging.