The Core Engineering - London - Associate - Software Engineering

The Core Engineering

The Core Engineering builds and operates the platforms, applications, data solutions, models, and analytics that power critical processes for The Core divisions of the firm (e.g., Risk, responsible for the risk profile of firm activities; Controllers, responsible for the financial control and reporting obligations; Compliance, responsible for the firm’s compliance, regulatory, and reputational risks; Corporate Treasury, responsible for the firm’s liquidity, funding, balance sheet, etc.; and Human Capital Management, responsible for attracting, developing, and managing a global workforce). A centralized engineering structure in support of The Core enables a common platform model and operating framework that promotes consistent governance and scalable solutions, leveraging cloud, AI, and machine learning for innovation and efficiency. The Core Engineering’s 2,000+ engineers and strats deliver engineering, data, analytics, and quantitative capabilities within six business units:

• Metrics & Analytics Platforms: responsible for the measurement and management of the firm’s risk, capital, and liquidity for The Core functions
• The Core Strats: responsible for the development and implementation of models and other quantitative methodologies, including the accuracy and attribution of modeled metrics
• Financials & Reporting: responsible for facilitating the production of the firm’s financials and a wide range of reporting functions
• Non-Financial Risk & Controls: responsible for non-financial risk and control processes
• Enterprise Platforms: responsible for platforms and applications that support critical operational processes across The Core such as payments, people processes, and procurement
• Shared Services: responsible for driving the adoption of consistent engineering strategy, including data platforms, cloud, and AI enablement, as well as the management of technology risk

Liquidity Execution Engineering

This specific role sits within Liquidity Execution Engineering under Metrics & Analytics Platforms. This role will provide a unique opportunity to develop your technical skills and gain exposure to one of the firm’s most complex and fascinating functions. Learning, teamwork, partnering with stakeholders, product ownership, working with very large data, designs, technical expertise and user experience; these are all aspects where you will build your skills and make your mark. A strong ownership mindset, an uncommon dedication to producing high-quality software, and a mindset of relentless improvement will all be key to your success in this role.

Responsibilities

• Hands-on end-to-end systems development in an Agile environment, from requirements analysis through coding, testing, UAT, implementation and maintenance.
• Partner with Finance stakeholders to understand business needs and translate them into process workflows, data requirements and specifications.
• Collaborate within and across software engineering teams to build reusable solutions that achieve the best long-term commercial outcome for Goldman Sachs and its clients.
• Harness AI coding tools (e.g. Claude Code, Codex, Devin) to accelerate development while maintaining high standards of quality and maintainability.

Basic Qualifications

• Bachelor’s degree or relevant experience in Computer Science, Mathematics, Electrical Engineering or related discipline
• Minimum of 1 year of experience in software development
• Strong technical and analytical skills; must be a self-starter
• Ability to thrive in a highly dynamic and collaborative environment working with a diverse set of colleagues and stakeholders across regions
• Strong communication skills (both written and spoken) and clear, logical thought process.
• Knowledge of data structures, algorithms and performance-oriented design
• Hands-on programming experience in Java or Python
• Experience with either relational databases, NoSQL DBs, or both

Preferred Qualifications

• Experience with Cloud Technologies - ideally AWS - e.g. S3, SQS, Lambda, Fargate
• Exposure to modern API development (e.g. REST, gRPC, GraphQL)
• Experience with big data concepts, such as Lakehouse, ETL data pipelines (e.g. Spark, AWS Glue)
• Experience developing distributed, micro services-based applications
• Experience with data modelling and curation for large-scale datasets
• Experience with near real time and event-based systems like Kafka
• Familiarity with CI/CD practices and the DevOps & SRE mindset
• Working knowledge of UNIX/Linux
• Experience of using Agentic AI coding tools - e.g. Claude Code, Codex, Devin
• Knowledge or interest in financial markets

We don’t expect every applicant to have expertise across all of the above, but you must be willing to learn new skillsets.

About Goldman Sachs

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.

We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

© The Goldman Sachs Group, Inc., 2025. All rights reserved.

Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.