AI Engineering - Vice President (Menlo Park, CA)

Goldman Sachs•Menlo Park, CA

1d•Onsite

About The Position

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. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets. Engineering, which is comprised of our Technology Division and global strategists groups, is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions. Want to push the limit of digital possibilities? Start here. Goldman Sachs is seeking an AI Engineer to join our dynamic GenAI Platform team. You will play a pivotal role in driving the next generation of AI adoption, moving from passive assistance to agentic automation. We are looking for engineers who can navigate modern AI by focusing on token optimization, long-context reasoning, and high-performance RAG pipelines. You will interact directly with business units to transform proprietary datasets into actionable intelligence through the GS AI Assistant and specialized autonomous agents.

Requirements

A master’s or Ph.D. degree in Computer Science, Machine Learning, Mathematics, Statistics, Physics, Engineering, Quantitative Finance, or equivalent relevant industry experience.
A minimum of 5 years of experience in the industry that demonstrates your expertise.
Extensive experience in software development for quantitative investment workflows in equities, fixed income, or multi-asset strategies.
Proficiency in contemporary programming languages like Python, C++, or Java.

Responsibilities

Design and deploy autonomous AI agents capable of independent planning, tool use, and multi-step task execution (e.g., automated research drafting, code migration, and regulatory summarization).
Architect and scale the GS AI Platform, the firm’s mission-critical "AI Platform" that provides a secure, multi-model backbone for autonomous agents and high-performance financial workflows.
Develop and integrate the latest agentic communication standards, including MCP (Model Context Protocol) for tool discovery, A2A (Agent-to-Agent) for multi-agent orchestration, and AGUI/A2UI for generative user interfaces.
Lead cross-functional projects to integrate AI into quantitative investment workflows, ensuring systems are reliable, maintainable, and secure.
Ensure all AI-based software systems adhere to the firm’s strict data privacy, ethics, and safety standards.