About the role
structured by ORIJob Description The Core Engineering Responsibilities 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…
What you will do
- Design, develop, and implement GenAI-driven solutions, including agentic frameworks for automating compliance processes, RAG pipelines, and embeddings of compliance knowledge bases.
- Explore diverse AI/ML problems, such as model fine-tuning, prompt engineering, and experimentation with different algorithmic approaches to address novel business challenges.
- Develop, test, and maintain high-quality, production-ready code.
- Collaborate effectively with compliance officers, legal counsel, and other stakeholders to understand business requirements and translate them into technical solutions.
- Participate in code reviews to ensure code quality, maintainability, and adherence to coding standards.
What they are looking for
- A Bachelor's, master’s or PhD degree in Computer Science, Machine Learning, Mathematics, or a similar field of study.
- Strong foundation in machine learning algorithms, including deep learning architectures (e.g., transformers, RNNs, CNNs)
- Proficiency in Python and relevant libraries/frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn.
- Demonstrated expertise in GenAI techniques, including but not limited to Retrieval-Augmented Generation (RAG), model fine-tuning, prompt engineering, AI agents, and evaluation techniques.
- Experience working with embedding models and vector databases.
- Experience with MLOps practices, including model deployment, containerization (Docker, kubernetes), CI/CD, and model monitoring.
- Strong verbal and written communication skills.
- Curiosity, ownership and willingness to work in a collaborative environment.
Nice to have
- Experience with Agentic Frameworks (e.g., Langchain, AutoGen) and their application to real-world problems.
- Understanding of scalability and performance optimization techniques for real-time inference such as quantization, pruning, and knowledge distillation.
- Experience with model interpretability techniques.
- Prior experience in code reviews/ architecture design for distributed systems.
- Experience with data governance and data quality principles.
- Familiarity with financial regulations and compliance requirements.
Benefits
- Access to petabyte scale of structured and unstructured data to fuel your AI/ML models, including textual data suitable for LLM applications.
- The opportunity to work with state-of-the-art LLM models and agentic framework.
- A collaborative environment where you can learn from and contribute to a team of experienced engineers and scientists.
- The chance to make a tangible impact on the firm's ability to manage risk and maintain its reputation.
Full posting text
Job Description
The Core Engineering
Responsibilities
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
YOUR IMPACT
Are you passionate about leveraging cutting-edge AI/ML techniques, including Large Language Models, to solve complex, mission-critical problems in a dynamic environment? Do you want to contribute to safeguarding a leading global financial institution?
OUR IMPACT
We are Compliance Engineering, a global team of engineers and scientists dedicated to preventing, detecting, and mitigating regulatory and reputational risks across Goldman Sachs. We build and operate a suite of platforms and applications that protect the firm and its clients.
We Offer
Access to petabyte scale of structured and unstructured data to fuel your AI/ML models, including textual data suitable for LLM applications.
The opportunity to work with state-of-the-art LLM models and agentic framework.
A collaborative environment where you can learn from and contribute to a team of experienced engineers and scientists.
The chance to make a tangible impact on the firm's ability to manage risk and maintain its reputation.
Within Compliance Engineering, we are seeking an experienced AI/ML Engineer to join our Engineering team. This role will focus on solving highly complex business problems using AI/ML techniques, incorporating latest emerging trends om building out vertical AI agents to run on data at massive scale.
How You Will Fulfill Your Potential
As a member of our team, you will:
Design, develop, and implement GenAI-driven solutions, including agentic frameworks for automating compliance processes, RAG pipelines, and embeddings of compliance knowledge bases.
Explore diverse AI/ML problems, such as model fine-tuning, prompt engineering, and experimentation with different algorithmic approaches to address novel business challenges.
Develop, test, and maintain high-quality, production-ready code.
Collaborate effectively with compliance officers, legal counsel, and other stakeholders to understand business requirements and translate them into technical solutions.
Participate in code reviews to ensure code quality, maintainability, and adherence to coding standards. Promote best practices for AI/ML development, including version control, testing, and documentation.
Stay current with the latest advancements in AI/ML platforms, tools, and techniques to solve business problems.
Qualifications
A successful candidate will possess the following attributes:
A Bachelor's, master’s or PhD degree in Computer Science, Machine Learning, Mathematics, or a similar field of study.
Preferably 3+ years AI/ML industry experience for Bachelor’s/Masters, 1 year for PhD with a focus on Language Models.
Strong foundation in machine learning algorithms, including deep learning architectures (e.g., transformers, RNNs, CNNs)
Proficiency in Python and relevant libraries/frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn.
Demonstrated expertise in GenAI techniques, including but not limited to Retrieval-Augmented Generation (RAG), model fine-tuning, prompt engineering, AI agents, and evaluation techniques.
Experience working with embedding models and vector databases.
Experience with MLOps practices, including model deployment, containerization (Docker, kubernetes), CI/CD, and model monitoring.
Strong verbal and written communication skills.
Curiosity, ownership and willingness to work in a collaborative environment.
Experience in some of the following is desired and can set you apart from other candidates:
Experience with Agentic Frameworks (e.g., Langchain, AutoGen) and their application to real-world problems.
Understanding of scalability and performance optimization techniques for real-time inference such as quantization, pruning, and knowledge distillation.
Experience with model interpretability techniques.
Prior experience in code reviews/ architecture design for distributed systems.
Experience with data governance and data quality principles.
Familiarity with financial regulations and compliance requirements.
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., 2026. 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.
Seniority level: Associate
Employment type: Full-time
Industries: Financial Services