VP, Software Engineering — Treasury Liquidity Platform

Goldman Sachs Group, Inc.; New York (NY); On-site; USD 180,000 - 280,000; Full time

Job summary

Goldman Sachs Group, Inc. in New York seeks a Vice President, Software Engineering within Corporate Treasury to design and deliver scalable software for liquidity projections, cash and collateral management, and funding strategies.

You will partner with Treasury stakeholders, develop front-to-back solutions, and mentor engineers while applying risk-aware, data-driven approaches to optimize firm liquidity and costs.

Qualifications

• Bachelor’s or Master’s degree in computer science, mathematics, electrical engineering or related technical discipline.
• Strong software development experience with data structures, algorithms and design.
• Ability to multi-task, manage stakeholders and work in a team.
• Designing complex, distributed scalable systems.
• Excellent communication with technical and business audiences; global exposure.
• Willingness to learn SecDB/Slang and proprietary risk systems.
• Ideally 5+ years IT industry experience.

Responsibilities

• Identify and measure risk using quantitative software solutions.
• Collaborate with business partners to enhance treasury systems and processes.
• Apply analytics to drive commercial outcomes and communicate clearly.
• Develop scalable architecture and SDLC compliant software.
• Work with traders to deliver real time, high value technology.

Skills

Java

Python

Distributed systems

Software design

Communication

SecDB/Slang

5+ years experience

Education

Bachelor's or Master's in CS/Math/EE

Tools

SecDB

Slang

Proprietary risk system

Job description

Goldman Sachs Group, Inc. in New York seeks a Vice President, Software Engineering within Corporate Treasury to design and deliver scalable software for liquidity projections, cash and collateral management, and funding strategies.

You will partner with Treasury stakeholders, develop front-to-back solutions, and mentor engineers while applying risk-aware, data-driven approaches to optimize firm liquidity and costs.