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Goldman Sachs
Goldman Sachs

The Goldman Sachs Group, Inc

AI Engineering, Vice President (New York, New Jersey, Toronto) at Goldman Sachs

RoleMachine Learning
LevelVp
LocationNew York, NY, United States
WorkOn-site
TypeFull-time
Posted1 day ago
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About the role

What We Do:

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.

Who We Look For

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.

Your Responsibilities

  • Agentic System Development:

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).

  • Platform Engineering:

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.

  • Protocol Implementation: 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.
  • Technical Leadership:

Lead cross-functional projects to integrate AI into quantitative investment workflows, ensuring systems are reliable, maintainable, and secure.

  • AI Governance:

Ensure all AI-based software systems adhere to the firm’s strict data privacy, ethics, and safety standards.

Required Qualifications:

  • 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.

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

Salary Range
The expected base salary for this New York, New York, United States-based position is $115000-$180000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end.

Benefits
Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings, as it is a core part of providing a strong overall employee experience. A summary of these offerings, which are generally available to active, non-temporary, full-time and part-time US employees who work at least 20 hours per week, can be found here.

Required skills

LLMs

RAG

Agentic systems

Prompt engineering

Python

Data integration

System design

AI platform engineering

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About Goldman Sachs

Goldman Sachs

The Goldman Sachs Group, Inc. is an American multinational investment bank and financial services company. Founded in 1869, Goldman Sachs is headquartered in the Battery Park City neighborhood of Manhattan in New York City, with regional offices in many international financial centers.

45,000+

Employees

Lower Manhattan

Headquarters

$80B

Valuation

Reviews

2 reviews

2.9

2 reviews

Work-life balance

2.5

Compensation

3.0

Culture

2.0

Career

4.0

Management

2.5

45%

Recommend to a friend

Pros

Amazing career growth opportunities

Chill management at some locations

Work-life balance valued in certain roles

Cons

Toxic workplace culture

Codependent atmosphere

Confusing interview process

Salary Ranges

20,304 data points

Junior/L3

VP

Junior/L3 · Data Scientist Analyst

0 reports

$146,500

total per year

Base

-

Stock

-

Bonus

-

$124,525

$168,475

Interview experience

4 interviews

Difficulty

3.5

/ 5

Duration

21-35 weeks

Experience

Positive 0%

Neutral 75%

Negative 25%

Interview process

1

Application Review

2

HR Screen/HireVue

3

Recruiter Screen

4

Superday/Panel Interview

5

Final Decision

Common questions

Behavioral/STAR

Technical Knowledge

Culture Fit

Past Experience

Case Study