AI Solutions Engineer — Data-Driven Wealth Management

The Goldman Sachs Group; Dallas (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Goldman Sachs is seeking an AI Solutions Engineer to design and deliver production AI systems within the WM data engineering team. You will work on cloud-native data tooling, LLM-powered workflows, and integration with services like S3, Databricks, Snowflake, Glue, Athena, MWAA.

You will collaborate with senior engineers, data architects, and business stakeholders, writing clean, tested code and ensuring responsible AI practices when handling sensitive financial data.

Qualifications

• 3+ years of software engineering experience with ML/AI application development.
• Proficiency in Java, Python, and SQL; hands-on experience with LLM APIs or agentic frameworks.
• Familiarity with agentic patterns: tool use, multi-step reasoning, and structured output generation.

Responsibilities

• Build and maintain AI-powered data engineering tools and LLM agents integrated with the WM data platform.
• Develop evaluation frameworks (LangSmith, RAGAS, PromptFoo) to measure AI output quality.
• Write well-tested production code with unit and integration tests for AI components.

Skills

Java

Python

SQL

LLM APIs

Analytical thinking

Tools

LangSmith

RAGAS

PromptFoo

LangChain

Airflow

Job description

Goldman Sachs is seeking an AI Solutions Engineer to design and deliver production AI systems within the WM data engineering team. You will work on cloud-native data tooling, LLM-powered workflows, and integration with services like S3, Databricks, Snowflake, Glue, Athena, MWAA.

You will collaborate with senior engineers, data architects, and business stakeholders, writing clean, tested code and ensuring responsible AI practices when handling sensitive financial data.