Global Banking

The OpportunityGoldman Sachs has embarked on one of its most ambitious engineering programs: the Consolidated Trade Ledger (CTL), a ground-up reimagining of the front-to-back architecture that underpins every trade the firm executes. CTL is a flagship initiative jointly sponsored by Global Markets and Engineering leadership, and it sits at the very heart of the firm's core technology strategy.
This new, cloud-native platform will deliver the capacity, extensibility, scalability, and innovation capabilities to power the next two decades of growth for Global Markets, while simultaneously driving significant operational efficiencies. The program follows an engineering-principles-first approach and represents a rare chance to define the foundational systems of a world-leading financial institution from the ground up.
As trading volumes continue to accelerate, we are building a small team of ambitious and highly experienced engineers to spearhead the migration of our entire global Equities trading business onto CTL. The RoleYou will work with a set of core CTL business services and adapt them for Equities Trading, creating capabilities that can be leveraged across Global Markets front, middle, and back office functions. This includes extending CTL's flexible data model to integrate seamlessly with existing production idioms, while meeting the diverse and often complex business requirements of a global 247 trading operation, while balancing stringent non-functional demands for availability, latency, and resilience.
Critically, you will lean heavily into AI-driven development. Using Goldman Sachs' AI tooling and agentic coding assistants, you will govern multiple AI agents, rapidly comprehend large legacy codebases, generate and assess production-quality code, and accelerate every phase of the software development lifecycle.
Your ImpactDrive a 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 CTL 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' Equities 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 DoDesign, 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 managementPartner 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 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 Qualifications8+ years of professional software development experience in Java (Java 17+ preferred), with strong command of concurrency, collections, and modern language featuresDemonstrated 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 productExperience building event-driven and distributed systems, including familiarity with messaging platforms (e.g., Apache Kafka), delivery guarantees, and resilience strategiesStrong SDLC practices: version control, CI/CD pipelines, automated build/test/deploy workflows, and code quality toolingSolid testing discipline: unit, integration, and acceptance testing with modern frameworksAbility to rapidly navigate, understand, and debug large and unfamiliar codebases — with and without AI assistanceExcellent communication and collaboration skills across technical and non-technical audiences in geographically distributed teamsPreferred Qual