About The Position

At Goldman Sachs, our Engineers don’t just make things – we make things possible.  Change the world by connecting people and capital with ideas.  Solve the most challenging and pressing engineering problems for our clients.  Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action.  Create new businesses, transform finance, and explore a world of opportunity at the speed of markets. Engineering, which is comprised of our Technology Division and global strategists’ groups, is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions.  Want to push the limit of digital possibilities?  Start here. Goldman Sachs Asset and Wealth Management Division: As one of the world's leading asset managers, our mission is to help our clients achieve their investment goals.  To best serve our clients' diverse and evolving needs, we have built our business to be global, broad, and deep across asset classes, geographies, and solutions. Within the Multi Asset Solutions (MAS) investing group, we seek to develop a first-in-class digital advice platform across 401(k), IRA, and brokerage accounts, to provide individuals with custom tailored investment strategies to meet their retirement objectives. Who We Look For Goldman Sachs Engineers are innovators and problem-solvers, building solutions in risk management, big data, mobile and more. We look for creative collaborators who evolve, adapt to change and thrive in a fast-paced global environment. Role Overview: A mid-level execution role focused on building, testing, and maintaining high-performance user interfaces while leveraging modern AI-assisted coding workflows.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
  • 3–5 years of professional experience in front-end web development, ideally within financial services.
  • Proficiency in TypeScript, JavaScript (ES6+), HTML5, and CSS3.
  • Hands-on experience with modern frameworks (Angular/React) and state management libraries (e.g., Redux).
  • Strong understanding of data structures, algorithms, and RESTful API integration.
  • Experience with version control systems, particularly Git.
  • Familiarity with the Software Development Lifecycle (SDLC) and associated tools for build, deployment, and testing.
  • Excellent communication and interpersonal skills, with the ability to collaborate effectively with technical and non-technical stakeholders.

Nice To Haves

  • Experience leveraging AI-augmented development tools to improve velocity and code quality.
  • Familiarity with wealth management concepts, portfolio construction, or trade execution workflows.
  • Experience with libraries like D3.js or Highcharts for rendering complex financial data.
  • Proficiency with testing frameworks (Jest, Cypress) and CI/CD pipelines in cloud environments (AWS/Azure).

Responsibilities

  • Develop, enhance, and maintain the firm’s front-end software solutions for PWM Advisor and PM Engineering teams using Angular.
  • Design and implement high-quality, scalable UI components and design systems that ensure visual consistency across wealth management platforms.
  • Partner with Product Managers, UX Designers, and Back-end Engineers to translate complex financial workflows into intuitive, responsive web experiences.
  • Actively participate in all phases of the Software Development Lifecycle (SDLC), including automated testing (unit, integration) and User Acceptance Testing (UAT).
  • Write clean, type-safe code (TypeScript) and participate in peer code reviews to maintain high standards of maintainability and performance.
  • Utilize AI coding assistants (e.g., Copilot, Devin, Claude Code) to accelerate boilerplate generation, refactoring, and unit test creation while ensuring code security and accuracy.
  • Identify and resolve front-end bottlenecks to ensure low-latency performance for data-heavy financial dashboards.
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