What We Do

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. Drive new businesses, redefine finance using AI, and seize opportunities at market speed.

In an era defined by AI, Engineering isn't just central - it's the driving force behind our business. Our dynamic environment demands innovative strategic thinking and immediate, impactful solutions. Ready to push the limits of digital possibility? Begin your journey here.

Who We Look For

Goldman Sachs Engineers are at the forefront of innovation, driving solutions as creative collaborators in a fast-paced global environment. We seek individuals who evolve, adapt, and thrive on challenging problems.

We are seeking a senior engineer who can lead at the frontier of cloud-native financial systems and AI-driven engineering - someone who is energized by hard problems, brings deep technical credibility, and wants to define what the next generation of platforms looks like.

Your Impact

• Drive strategic transformation: Work alongside domain experts to understand existing production processes, challenge long-held assumptions that may no longer hold in a cloud-centric, AI-driven world, and define and deliver the requirements for efficient AI integration.
• Multiply your output with AI: Orchestrate AI coding agents (e.g., Claude Code, GitHub Copilot, Devin, Gemini Code Assist) across all stages of the SDLC while maintaining mastery, quality, and production fitness over all AI-generated work product.
• Deliver outsized business value: Position Goldman Sachs' trading business to handle orders-of-magnitude higher volumes at lower operational costs, directly contributing to the firm's competitive and commercial edge.
• Build for the future: Design and implement high-availability, multi-region, event-driven services on a modern cloud-native platform, setting the architectural standard for years to come.

What You Will Do

• Design, build, and operate high-availability, multi-region, cloud-native services with security and comprehensive observability (metrics, distributed tracing, structured logging) built in at every layer.
• Develop event-driven architectures, multi-stage processing pipelines, and optimized data paths for high-throughput trade lifecycle management.
• Partner with engineers, domain experts, and global stakeholders to understand, model, and digitize the firm's business processes, challenging entrenched practices and driving modernization across teams.
• Manage the full lifecycle of software components, from requirements analysis through design, development, testing, and release, in line with robust SDLC and Agile best practices.
• Innovate creative solutions to complex business and technical problems, building reusable capabilities that can be leveraged across Global Banking & Markets' front, middle, and back office functions.
• Multiply your impact with a modern, AI-centric toolchain, orchestrating AI coding agents across all stages of the SDLC to rapidly comprehend large codebases, generate production-quality code, and accelerate delivery.

Required Qualifications

• 6+ years of professional software development experience in Java (Java 17+ preferred), with strong command of concurrency, collections, and modern language features
• Demonstrated experience with AI-assisted engineering tools (e.g., Claude Code, GitHub Copilot Agent Mode, Devin, Gemini Code Assist), including the ability to govern AI agents, critically assess their output, and maintain quality over AI-generated work product.
• Experience building event-driven and distributed systems, including familiarity with messaging platforms (e.g., Apache Kafka), delivery guarantees, and resilience strategies.
• Strong SDLC practices: version control, CI/CD pipelines, automated build/test/deploy workflows, and code quality tooling.
• Solid testing discipline: unit, integration, and acceptance testing with modern frameworks.
• Ability to rapidly navigate, understand, and debug large and unfamiliar codebases - with and without AI assistance.
• Excellent communication and collaboration skills across technical and non-technical audiences in geographically distributed teams.