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Goldman Sachs

Advises on mergers and trades stocks and bonds

Quantitative Enablement Platform Engineer - Global Banking & Markets, Vice President

Quantitative DevelopmentUpdated on Nov 14
Full-timeWarsaw, PolandNo salary listedIn-person

About the Job

Requirements

  • At least 8 years of experience 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.
  • Ability to work closely with engineering and business stakeholders.
  • Curiosity about markets, data, and complex systems, with motivation to solve technical problems at the intersection of engineering and quantitative research.
  • Interest in rapid experimentation, continuous learning, and building platforms that influence investment research, signal discovery, and trading decision-making.

Responsibilities

  • Partner with quantitative researchers, portfolio managers, traders, and engineering teams to define and deliver research capabilities, platform and infrastructure, AI-assisted workflows, and scalable compute for signal discovery, experimentation, back testing, deployment, and production monitoring.
  • Build high-throughput distributed systems that process market, transactional, and alternative data at petabyte scale while maintaining low latency, resiliency, and operational excellence.
  • Develop research workflows incorporating large language models, agentic systems, model context protocols, and modern machine learning infrastructure.
  • Build AI-native research capabilities combining large language models, agentic systems, knowledge graphs, vector search, quantitative datasets, and experimentation frameworks.
  • Drive architecture, reliability, observability, automated testing, and software development best practices across a globally distributed platform.
  • Own critical platform capabilities from concept and architecture through implementation, adoption, and production operations, and help shape long-term platform strategy and engineering standards.

Desired Qualifications

  • Experience in quantitative trading, market structure, electronic trading, or fintech.
  • Experience developing machine learning, generative AI, or agentic AI platforms.
  • Experience with 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, and large-scale time-series data stores or similar tools supporting quantitative research workflows.
  • An advanced degree in Computer Science, Engineering, Mathematics, or a related quantitative discipline.

About the Company

Goldman Sachs

Advises on mergers and trades stocks and bonds

Goldman Sachs advises companies and governments on mergers, raises money for them by selling their stocks and bonds, and trades securities for big investors such as hedge funds and pension funds. It led Ford Motor's 1956 stock market debut, then the largest share sale in US history. Traders buy and sell stocks, bonds, currencies, and commodities for clients and lend them money, while bankers earn a fee on each deal they advise on or arrange. Its asset and wealth management arm invests for institutions and wealthy families and charges fees based on the money it oversees. The firm was founded in 1869, when it began brokering short-term IOUs for New York merchants, and it is based in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1869

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