Software 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, Controllers, Compliance, Corporate Treasury, and Human Capital Management). 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.
• 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.
• Shared Services: responsible for driving the adoption of consistent engineering strategy.

The Core Engineering Shared Services AI team operates as an internal forward-deployed AI engineering function, embedding with The Core business teams to identify priority workflows, prototype agentic AI solutions, and productionize cloud-native applications that deliver measurable business impact. This hands-on role combines client-facing problem discovery, rapid engineering execution, production AI architecture, and structured transition to receiving teams that will operate and extend the solutions over time.

As an AI Application Engineer, you will work directly with internal business and engineering partners to convert ambiguous operating problems into secure, reliable AI products. You will define where agents should act, where they should assist, and where human approval or control gates are required, then design and deliver solutions that are adopted in real workflows and can be supported in production.

Key Responsibilities

• Rapid Prototyping & Application Delivery: Lead the design, build, deployment, and operationalization of cloud-native AI applications.
• Business Partnership & Solution Architecture: Partner with business and engineering teams to identify high-impact AI opportunities.
• Forward-Deployed AI Engineering: Embed with The Core business teams to map workflows and identify pain points.
• Production AI/ML Integration: Build AI applications using LLM APIs and other technologies required for production use.
• Cloud, DevOps & MLOps Execution: Apply cloud-native services and practices to ensure applications are scalable and resilient.
• Knowledge Transfer & Enablement: Document solutions and mentor receiving teams.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related quantitative field.
• 9+ years of hands-on software engineering experience.
• Strong proficiency in Python, Java, or Go.
• Proven experience translating complex business requirements into cloud-optimized application architectures.
• Experience operating in a forward-deployed or internal client-facing engineering model.
• Extensive experience with major cloud platforms such as AWS, Azure, or GCP.
• Demonstrated experience integrating LLM or AI/ML capabilities into production applications.
• Excellent communication and collaboration skills.

Preferred Experience

• Experience building agentic AI systems.
• Experience implementing agent observability and controls.
• Experience optimizing production AI systems.

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.