We are looking for an AI Engineer with over 5 years of experience to join the Liquidity Risk technology team. The role focuses on designing, building, and deploying AI-driven solutions to enhance liquidity risk monitoring and decision support. You will collaborate with liquidity risk managers and quantitative teams to translate complex risk problems into scalable AI systems. This position offers an opportunity to work at the intersection of AI, engineering, and liquidity risk on a global scale.

• 5+ years of professional experience as an AI Engineer in a production environment.
• Hands-on experience in integrating LLM models using agents and developing monitoring and observability tools for those agents.
• Experience with the AWS Bed Rock platform, especially using AWS Agent core for deploying agents.
• Experience in developing agents using Google ADK or Lang Graph frameworks and deploying them on AWS.
• Exposure to distributed computing frameworks and workflow orchestration tools such as Airflow.
• Strong proficiency in Python and experience with ML/AI libraries such as PyTorch or similar.
• Solid understanding of machine learning fundamentals, including model selection, bias-variance trade-offs, and evaluation techniques.
• Experience working with large, structured datasets using SQL and distributed data platforms.

• Design, develop, and deploy machine learning and AI models to support liquidity risk metrics and stress scenarios.
• Build end-to-end AI pipelines, including data ingestion, feature engineering, model training, validation, deployment, and monitoring.
• Apply supervised, unsupervised, and time-series modeling techniques to large-scale financial and transactional datasets.
• Partner with liquidity risk managers and quantitative teams to translate regulatory and business requirements into AI-driven solutions.
• Optimize agents' performance, scalability, and reliability in distributed and cloud-based environments.
• Contribute to the firm’s AI engineering standards, including testing, model documentation, and production controls.
• Mentor junior engineers and contribute to code reviews, design discussions, and architecture decisions.

• Employees at Goldman Sachs are often offered comprehensive benefits, including medical, dental, life and disability coverage, generous vacation and holidays, and robust wellness resources such as EAP counseling, medical advocacy, on-site/virtual health services, and fitness support. Financial perks typically include retirement savings programs, live financial education, education support, and wealth-creation opportunities through equity awards and select investment programs. Many locations also provide family benefits (childcare resources, parental and family leaves, adoption/surrogacy support) and flexible work options like part-time schedules, job sharing, telecommuting, and alternate hours.