
Asset &Wealth Management-Wealth AI Engineering - Associate
at Goldman Sachs
Posted 13 days ago
No clicks
- Compensation
- Not specified USD
- City
- Dallas
- Country
- United States
Currency: $ (USD)
We are seeking a GenAI Developer to join Goldman Sachs' Wealth Management AI initiatives, focusing on applied generative AI. The role involves developing and implementing AI solutions across Wealth Management, leveraging Retrieval-Augmented Generation, vector stores, prompt engineering, and various Large Language Model APIs. You will work with stakeholders to translate requirements into AI solutions, conduct research and experiments to advance AI capabilities, and help drive innovation within the Wealth Management division.
What We Do
At Goldman Sachs, we connect people, capital and ideas to help solve problems for our clients. We are a leading global financial services firm providing investment banking, securities and investment management services to a substantial and diversified client base that includes corporations, financial institutions, governments and individuals.
Job Description
We are seeking a highly skilled GenAI Developer to join our dynamic, global team. The ideal candidate will have a strong background in applied generative AI. This role will involve developing and implementing AI solutions, working with various technologies, and collaborating with cross-functional teams to drive innovation. The GenAI Developer will play a crucial role in advancing our GenAI capabilities and contributing to the success of our Wealth Management division.
Key Responsibilities
- Work with stakeholders to understand requirements and deliver AI solutions across several domains in Wealth Management.
- Stay updated with the latest advancements in AI and machine learning technologies.
- Conduct research and experiments to improve AI capabilities within the division.
Required Competencies
- Retrieval-Augmented Generation (RAG): Experience in developing and implementing RAG models to enhance information retrieval and generation tasks.
- Vector Stores: Knowledge of Vector Stores for efficient data storage and retrieval.
- Prompt Engineering: Skills in designing and optimizing prompts for AI models to improve accuracy and relevance.
- Large Language Model APIs (LLM APIs): Understanding of different LLMs, both commercial and open source, and their capabilities (e.g., OpenAI, Gemini, Llama, Claude).
- Programming Languages: Proficiency in Python, Java, or other relevant programming languages.
- Data Analysis: Strong analytical skills and experience with data analysis tools.
- Problem-Solving: Excellent problem-solving abilities and attention to detail.
- Communication: Strong verbal and written communication skills.
Preferred Competencies
- Graph RAG: Proficiency in using Graph RAG for complex data relationships and insights.
- Knowledge Graphs: Expertise in building and managing Knowledge Graphs to represent and query complex data structures.
- Machine Learning Frameworks: Experience with TensorFlow, PyTorch, or similar frameworks.
- Experience with cloud platforms such as AWS, Google Cloud, or Azure.
- Familiarity with natural language processing (NLP) and computer vision technologies.
- Previous experience in a similar role or industry.
- Master’s or Ph.D. in Computer Science, Data Science, or a related field.











