Vice President, Software Engineering

Goldman Sachs

Quick summary

Work type
On-site
Location
Dallas, TX
Posted
1 day ago

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Salary context

How this pay compares to similar roles

Similar $182k
$134k most similar roles pay here $222k

This listing doesn't post a salary. Most similar roles pay $157,200–$206,100.

Based on 240 similar postings.

Employer

About Goldman Sachs

Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.

Goldman Sachs currently has 187 open roles on FindRole.

Listed pay typically runs $130,000–$250,000 across 60 roles with salary data.

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At a glance

TL;DR · Vice President, Software Engineering

The role of AI Engineer at Corporate Treasury in Dallas is a senior position aimed at enhancing liquidity risk management through advanced AI solutions. As part of the Liquidity Risk technology team, you will design and deploy machine learning models to support risk metrics, stress testing, and forecasting, working closely with risk managers and quantitative teams to develop scalable AI systems. Key responsibilities include building end-to-end AI pipelines, applying various modeling techniques on large financial datasets, and optimizing performance in cloud environments. The ideal candidate has 5+ years of experience in production settings, proficiency in Python and frameworks like PyTorch, and hands-on experience with AWS Bedrock and distributed computing tools. This role offers a unique opportunity to work at the intersection of AI, engineering, and liquidity risk management on a global scale.

What you'll do

  • Design, develop, and deploy machine learning models for liquidity risk metrics and forecasting.
  • Build end-to-end AI pipelines from data ingestion to model deployment and monitoring.
  • Apply various modeling techniques to large financial datasets for regulatory compliance.
  • Translate complex business requirements into scalable AI-driven solutions with quantitative teams.
  • Optimize AI systems for performance in distributed and cloud-based environments.
  • Contribute to the firm’s AI engineering standards, including testing and documentation practices.

What we're looking for

  • 5+ years of experience as an AI Engineer in a production environment.
  • Expertise in designing and deploying machine learning and AI models for financial applications.
  • Proficiency in Python and ML/AI libraries such as PyTorch or similar.
  • Experience with AWS Bedrock platform, including AWS Agent core for agent deployment.
  • Hands-on skills in developing agents using Google ADK or Lang Graph frameworks on AWS.
  • Strong understanding of machine learning fundamentals and large-scale data processing.

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