Senior Software Engineer, Global Banking & Markets, Securities Settlement Engineering

Goldman Sachs•Salt Lake City, UT

About The Position

Within the firm's Global Banking & Markets business, the Securities Settlement Engineering team operates at the intersection of finance and technology, implementing innovative solutions to enhance the post-trade processing landscape. Our team is responsible for designing, developing, and maintaining high-performance software solutions that facilitate the settlement of equities and fixed income instruments, processing millions of events and thousands of users daily. There is a current focus on migrating existing systems to a strategic platform, with a foundation built upon an event-sourcing architecture using public cloud and serverless solutions, to enhance the scalability and resilience of the settlement processes and guaranteeing capacity for future growth. Collaboration with various stakeholders, including trading desks, operations teams, and other Engineering groups, ensures that the systems meet the evolving needs of the business and integrate seamlessly with other platforms. Our team primarily uses Java for software development, while also leveraging other languages, tools, and frameworks for specific tasks. We employ a microservices architecture and RESTful APIs to build modular and scalable systems and embrace DevOps practices to ensure continuous integration and delivery. A global team located across seven regions, the Securities Settlement Engineering team fosters a collaborative and inclusive work environment, encouraging team members to share ideas and contribute to continuous improvement. Our work is critical to Goldman Sachs' success, as it ensures the efficient and accurate settlement of trades, helps the firm manage risk and comply with regulations, and establishes exceptional service for our clients.

Requirements

Proven track record as a senior software engineer with end-to-end ownership of complex, cloud-based production systems on AWS.
Deep hands-on experience in Java building distributed calculation engines and event-driven services; comfort working across a polyglot stack.
Experience designing and operating cloud-native platforms using microservices, gRPC/REST APIs, and managed AWS services (Fargate, Lambda, Step Functions, Aurora, ElastiCache, S3).
Demonstrated experience using AI agents and AI-based tooling for enterprise software development – code generation, automated analysis, diagnostics, or migration validation.
Strong testing discipline using modern frameworks and patterns, with an instinct for writing code that is correct by construction.
Deep understanding of distributed systems – data consistency, failure modes, observability, and the operational realities of running financial infrastructure at scale.
Exceptional communication skills and the ability to influence engineers, architects, and business stakeholders with clarity and conviction.
Bachelor's degree in computer science, engineering, or a related field.

Nice To Haves

AWS serverless and managed infrastructure: Fargate, Lambda, Step Functions, Aurora PostgreSQL, ElastiCache Redis, S3, EventBridge, CloudWatch.
AI-enhanced engineering workflows: building developer or operational tooling powered by AI for diagnostics, reconciliation, code generation, or automated validation.
Graph-based execution orchestration: DAG scheduling, topological sort, data dependency resolution with configurable wait, bypass, and fallback semantics.
Platform migration at scale: migrating monolithic on-premises systems to cloud-native architectures with incremental rollout, dual-run reconciliation, and zero-downtime cutover.
Infrastructure-as-code: AWS CDK (TypeScript) and DevOps practices for large-scale, multi-region platform deployments.
Modern build systems: polyglot monorepo tooling with remote execution, container image pipelines, and protobuf code generation.
Containerization and orchestration: Docker, Fargate task definitions, dual-mode services (one-shot compute + long-running daemon).
Financial domain expertise: Post-trade processing, or high-volume financial risk systems.
AI fluency: agentic AI workflows, prompt engineering and a point of view on how AI will reshape enterprise software engineering.

Responsibilities

Lead the design and implementation of cloud-native post trade platform. Building systems that are correct, fast, and operationally excellent.
Take full ownership of production services from design through deployment and incident response. Being the person the team trusts to make the right call when it matters.
Own key workstreams in the transformation to AWS/GCP, ensuring automated reconciliation, incremental rollout, and rigorous dual-run validation.
Champion the use of AI agents and AI-enabled tooling across the team – for specification, implementation, testing, reconciliation analysis, and operational diagnostics. Help the team move from "AI-curious" to "AI-native."
Guide architectural decisions across the polyglot codebase, review critical code, define data dependency and orchestration patterns, and mentor engineers who want to grow into senior technical leaders.
Work closely with business, risk, trading, and clearing teams to translate business requirements into technology-driven automation, intelligent tooling, and measurable operational improvements.
Contribute to CDK infrastructure stacks, CI/CD pipelines, container image pipelines, and multi-region deployment automation — because owning a service means owning how it gets to production.