We are seeking an AI Engineer with 5+ years of experience to join the Liquidity Risk technology team. In this role, you will design, build, and deploy AI‑driven solutions that enhance liquidity risk monitoring, stress testing, scenario generation, and decision support. You will work closely with liquidity risk managers, quantitative teams, and engineering partners to translate complex risk problems into scalable, production‑ready AI systems.
Key Responsibilities- Design, develop, and deploy machine learning and AI models to support liquidity risk metrics, stress scenarios, early‑warning indicators, and forecasting.
- 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.
- 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 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 (e.g., 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 (cloud data warehouses).
- Opportunity to work at the intersection of AI, engineering, and liquidity risk at a global scale.
- High‑impact role influencing how the firm measures and manages liquidity under stress.
- Collaborative environment with exposure to senior risk managers, quants, and technology leaders.
- Ongoing learning, development, and career progression within the Liquidity and Engineering organizations.
Skills Required
- 5+ years of professional experience as an AI Engineer in a production environment.
- Hands-on experience integrating LLM models using agents and developing monitoring and observability tools for those agents.
- Experience with AWS Bedrock platform, especially using AWS Agent Core for deploying agents.
- Experience developing agents using Google ADK or LangGraph frameworks and deploying them on AWS.
- Exposure to distributed computing frameworks and workflow orchestration tools (e.g., 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 (cloud data warehouses).
Goldman Sachs Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Goldman Sachs and has not been reviewed or approved by Goldman Sachs.
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Healthcare Strength — Coverage includes medical, dental, vision, disability, life and accident insurance, with multiple plan options and most premiums subsidized; coverage often starts on day one. Wellness resources, on-site health centers in some locations, and EAP access reinforce the depth of health support.
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Parental & Family Support — Family care includes on-site childcare in some offices, expectant parent resources, and transitional programs for returning parents. Feedback suggests parental leave is very generous, with reports of around 20 weeks paid leave and stipends for adoption, surrogacy, and fertility-related services.
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Retirement Support — The firm provides a 401(k) plan with employer matching contributions and broad financial education to help employees plan for retirement. Resources also support saving for education and preparing for unexpected events.
Goldman Sachs Insights
What We Do
At Goldman Sachs, we believe progress is everyone’s business. That’s why we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, Goldman Sachs is a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices in all major financial centers around the world. More about our company can be found at www.goldmansachs.com
