Core Engineering, Knowledge Graph Software Engineer, Associate/ Vice President, Singapore

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Developer Journey Strategy at Goldman Sachs

The Developer Journey Strategy focuses on investing in the developer experience to minimize friction, promote standardization, and leverage artificial intelligence (AI) to enable seamless delivery. By streamlining processes, implementing consistent practices, and integrating AI-driven tools and solutions, we empower developers to efficiently build and run products and platforms. This strategy aims to enhance productivity, foster innovation, and ensure high-quality outcomes by providing developers with the advanced tools, resources, and support they need to succeed. The incorporation of AI not only automates routine tasks and optimizes workflows but also provides predictive insights and intelligent recommendations, further enhancing the development process.

SDLC Engineering

Part of Goldman Sachs’ Core Engineering group is to provide best-in-class language support and tooling for our engineering community to facilitate building, testing, and deploying products. We strive to improve product quality, developer productivity, and collaboration. Our goal is to innovate and create technology solutions that impact the firm's bottom line. By joining us, you will be part of a diverse global technical team focused on solving critical business problems. You will work at the heart of the developer experience, ensuring code written by thousands of GS engineers is versioned securely, reviewed expertly, compiled quickly, tested comprehensively, and distributed widely.

What You Will Be Working On

The Knowledge Engineering team builds platforms to access, understand, and leverage institutional knowledge effectively. Our mission is to transform information management and retrieval across the firm, driving innovation and productivity through data and AI solutions. We seek a highly skilled Engineer to join our Knowledge Engineering team. This role focuses on designing, building, and maintaining our internal knowledge graph, a core component for AI-driven capabilities. Leveraging Large Language Models (LLMs) and vendor products, you will create a unified, intelligent system that democratizes access to organizational data, enhances decision-making, and supports strategic initiatives.

Responsibilities

• Design, develop, and maintain data retrieval systems to support Generative AI infrastructure with organizational and system knowledge from unstructured data.
• Lead the modeling and evolution of the knowledge graph, ensuring it is efficient, scalable, and accurate.
• Ensure conformance with firm security and AI standards.
• Integrate AI systems with the knowledge graph to improve reasoning, semantic search, and data retrieval, minimizing hallucinations.
• Work with vendor products, configuring integrations with internal data sources to build a unified enterprise data retrieval system.
• Collaborate with product managers, AI/ML engineers, and stakeholders to align data solutions with business needs.
• Maintain data quality, integrity, and security within the knowledge graph with validation and monitoring mechanisms.
• Contribute to improving data engineering best practices, tools, and processes within SDLC Engineering.

Basic Qualifications

• Bachelor's or Master's in Computer Science, Data Engineering, or related field.
• At least 5 years (Associate) or 10 years (VP) experience in data engineering, focusing on scalable distributed systems.
• Proficiency in Python or Java.
• Knowledge of modern network stacks, including gateways, load balancing.
• Experience with cloud platforms (AWS, GCP, Azure).
• Strong understanding of data structures and algorithms.
• Familiarity with SDLC processes and tools.

Preferred Experience

• Experience with LLMs and enterprise search or knowledge management applications.
• Knowledge of LLM communication protocols (MCP, A2A).
• Experience with enterprise AI search platforms leveraging knowledge graphs.
• Proven experience designing and implementing production-grade knowledge graphs.
• Experience with Retrieval Augmented Generation (RAG) and prompt engineering for LLMs.
• Knowledge of data governance, metadata management, and data cataloging.

About Goldman Sachs

Goldman Sachs is a leading global investment banking, securities, and investment management firm, committed to diversity, inclusion, and professional growth. Founded in 1869 and headquartered in New York, we operate worldwide. We offer opportunities for personal and professional development, wellness, and benefits. Learn more at GS.com/careers.

We provide reasonable accommodations for candidates with disabilities during the recruiting process. More info:

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Goldman Sachs is an equal opportunity employer.