Vice President – Quantitative Platform Software Engineer

Job Description Your Impact The future of quantitative investing belongs to platforms that turn massive data into ideas, signals, and decisions in real time. Goldman Sachs has the raw materials few firms can match: one of the deepest sets of market, transactional, and alternative data in finance, and one of the largest concentrations of quantitative talent anywhere; traders, researchers, strategists, and systematic PMs across global markets. What we are building is the platform that connects the two - compressing the path from research idea to live trading strategy from weeks to hours, for every researcher at the firm, on a single platform. As an engineer, your work will directly influence how quantitative researchers, and traders discover signals, test investment ideas, build capabilities that improve and translate research velocity, support alpha generation and strengthen into production trading decisions. What You'll Do Build the Platform for Quantitative Research Partner directly with quantitative researchers, portfolio managers, traders, and engineering teams to define and deliver high impact research capabilities, building the platform, infrastructure, AI assisted workflows, and scalable compute that accelerate signal discovery, experimentation, back testing, deployment, and production monitoring, reducing the time from idea to production from weeks to hours. Engineer at Scale Build high throughput distributed systems capable of processing petabytes of market, transactional, and alternative data while maintaining low latency, resiliency, and operational excellence. Enable AI First Research Develop next generation research workflows that incorporate large language models, agentic systems, model context protocols (MCP), and modern machine learning infrastructure to accelerate discovery and insight generation. Build AI native research capabilities that combine large language models, agentic systems, knowledge graphs, vector search, quantitative datasets and experimentation frameworks to make research workflows faster, more discoverable and more scalable. Raise the Engineering Bar Drive architecture, reliability, observability, automated testing, and software development best practices across a globally distributed platform. Own critical platform capabilities end to end, from concept and architecture through implementation, adoption and production operations, with the opportunity to shape long term platform strategy and engineering standards. What You'll Work On Real time streaming data platforms using Kafka, Flink, Spark, and cloud native technologies Distributed computing systems for large scale Quantitative research enablement and simulation AI and machine learning infrastructure, including training, inference, feature management, and model lifecycle tooling Agentic and generative AI applications for quantitative workflows Cloud native Software Engineering leveraging AWS, and modern data architectures Low latency systems supporting research, analytics, and trading use cases Research platform capabilities including back testing frameworks, experiment tracking, feature stores, meta data discovery, distributed research compute, Lakehouse architectures, ClickHouse, vector search, knowledge graphs and large scale timeseries platforms What We're Looking For 8+ years’ experience with a proven track record in building and operating large scale distributed systems Strong software engineering skills in Python, Java, Scala, or C++ Deep understanding of cloud native architectures and modern infrastructure platforms Experience building data intensive applications, streaming systems, or machine learning platforms Strong collaboration and communication skills with the ability to work closely with both engineering and business stakeholders Intellectually curious about markets, data and complex systems, with the motivation to solve difficult technical problems at the intersection of engineering and quantitative research Excited by rapid experimentation, continuous learning and building platforms that directly influence investment research, signal discovery and trading decision making Preferred Experience Quantitative trading, market structure, electronic trading, or fintech experience Machine learning, generative AI, or agentic AI platform development High performance computing, real time analytics, or large scale data platforms Experience with modern research data platforms and high performance analytics technologies, such as ClickHouse, Databricks, Lakehouse architectures, distributed compute frameworks, large scale time series data stores, or similar tooling used to support quantitative research workflows Advanced degree in Computer Science, Engineering, Mathematics, or a related quantitative discipline. Why Goldman Sachs You will join a team building strategic capabilities that sit at the center of Goldman Sachs' quantitative and electronic trading businesses. The platform you build will influence how research is conducted, how models are developed, and how ideas become production trading strategies across global markets. This role combines the scale and complexity of a leading technology company with the impact, pace, and intellectual rigor of one of the world's premier financial institutions. About Goldman Sachs At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities, and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We’re committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers. We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html © The Goldman Sachs Group, Inc., 2023. All rights reserved. Goldman Sachs is an equal opportunity employer and does not discriminate based on race, color, religion, sex, national origin, age, veterans' status, disability, or any other characteristic protected by applicable law. Goldman Sachs is an equal opportunity employer.