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.