Job Overview
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Job Description
About Us
At Goldman Sachs, our Engineers don't just make things — we make things possible. The WM Data Engineering team within Asset & Wealth Management builds the cloud-native data platform that underpins Wealth Management globally — spanning Lakehouse architecture on AWS, ETL/ELT pipelines, data governance, and AI-powered tooling that accelerates how we build and operate at scale.
Our AI Solutions Engineering function designs and delivers intelligent agent-based workflows and LLM-powered applications that transform how engineers and business teams work across the WM Data ecosystem.
Who We Look For
We are seeking a motivated AI Solutions Engineer to contribute to the design and delivery of production AI systems within a data engineering organization. You are intellectually curious, write clean tested code, and are excited about building AI applications at the intersection of large language models and real-world data infrastructure.
Responsibilities
- Build and maintain AI-powered data engineering tools — LLM agents for pipeline generation, schema mapping, data quality analysis, and migration — integrated with the WM data platform (S3, Databricks, Snowflake, Glue, Athena, MWAA).
- Build and iterate on evaluation frameworks (LangSmith, RAGAS, PromptFoo) to measure and improve AI output quality across data engineering workloads.
- Write well-tested, production-quality code with comprehensive unit and integration tests for AI components.
- Implement responsible AI practices in every system: output guardrails, prompt injection defenses, PII handling, and audit logging — especially critical when operating on sensitive financial data.
- Implement and maintain backend services and APIs that expose AI-driven data tooling platform engineers and internal stakeholders.
- Collaborate with senior engineers, data architects, and business stakeholders to scope requirements, prototype solutions, and ship iteratively.
- Actively seek feedback, grow technical breadth across AI and data engineering, and contribute to team knowledge-sharing.
Key skills/competency
- AI Solutions Engineering
- LLM Agents
- Data Engineering
- Cloud Data Services
- Python
- Java
- SQL
- Responsible AI
- Software Engineering
- AWS
How to Get Hired at Goldman Sachs
- Tailor your resume: Highlight relevant experience in AI, LLMs, Python, Java, SQL, and data engineering.
- Showcase your projects: Detail your contributions to building AI applications or data pipelines.
- Understand the role: Emphasize your ability to implement responsible AI and work with cloud data services.
- Prepare for technical interviews: Brush up on coding, system design, and AI/ML concepts.
- Research Goldman Sachs: Align your application with their values and commitment to innovation.
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