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Vice President role: Lead high‑latency C++ engineering & quantitative research for EMM Cash Trading at Goldman Sachs.
Drive ETF market‑making, own trading infra, blend software & data science in NYC.
Goldman Sachs | Electronic Market Making – Software Engineer – Vice President
Location: New York, NY | Level: Vice President | Team: Electronic Market Making (EMM) – Cash Trading
About the Team
The Electronic Market Making Cash Trading team systematically provides liquidity in US Equities and ETFs, both on-exchange and to low-touch client flow. The team leverages quantitative research combined with low-latency trading infrastructure to develop and implement automated trading and risk management strategies.
We're a small team that demands a high level of ownership and accountability from each contributor, while strongly emphasizing collaboration and transparency. Engineers on the team are deeply involved in both software and strategy development. We are seeking a dedicated and ambitious engineer who thrives in a challenging environment and wants to make a meaningful impact at the firm.
About the Role
This is a high-impact VP-level role central to the next phase of the EMM franchise. A key business priority you will help drive is expanding our footprint — broadening the ETF products where EMM can act as a Lead Market Maker (LMM), including products referencing private assets, options, and a wider set of foreign underliers, while enhancing on-exchange marketing system performance.
We are looking for a versatile engineer who combines all three of the following skillsets — someone who can write low-latency production code, structure and analyze large data sets, and bring quantitative rigor to financial modeling. This is not a narrowly scoped role: the ideal candidate moves fluidly between software engineering, data analytics, and quantitative research, and is equally comfortable owning infrastructure as they are shaping strategy.
1. Low‑Latency C++ Software Engineering
- Proven experience developing low‑latency C++ applications
- Trading systems experience is useful but not essential
- Ability to own projects independently with meaningful responsibility
- Comfort working in a tight development-to-production feedback loop
2. Data Analytics for Research & Production Systems
- Strong software engineering capability
- Professional or academic experience structuring and analyzing large data sets
- Ability to build and maintain research infrastructure that informs production strategy
3. Quantitative & Financial Modeling
- Experience working with financial risk models
- Familiarity with financial modeling techniques
- Strong quantitative and mathematical grounding
Key Responsibilities
- Design, develop, and maintain reliable trading components and critical low‑latency infrastructure
- Support the expansion of ETF LMM capabilities across new and more complex product sets (private assets, options, foreign underliers)
- Enhance on‑exchange marketing system performance
- Take an active interest in shaping strategy decisions beyond pure technical implementation
- Collaborate openly in a team environment where ideas are discussed and challenged
Basic Qualifications
- Bachelor's/Master's degree in a STEM field with 5 to 10 years of experience developing software architecture in C/C++
- Strong track record of designing, developing, and maintaining reliable trading components and critical infrastructure
- Demonstrates consistent quality in a fast-paced environment with quick turnaround from testing to production implementation
- Highly conscientious in maintaining operational robustness while evolving current architecture
- Thrives in a collaborative setting where ideas are openly discussed and challenged
- Expected to take an active interest in shaping strategy decisions beyond technical implementation
Preferred Qualifications
- Experience with statistics and data‑science methodologies
- Experience with Python and data‑science packages (e.g., NumPy, scikit‑learn)
- Experience building and maintaining high‑performance research infrastructure for large data inputs
- Experience optimizing high‑volume, low‑latency trading components
- Experience working with financial risk models and financial modeling techniques
Salary Range
The expected base salary for this New York, NY, United States-based position is $150000-$300000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end.
Benefits
Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings, as it is a core part of providing a strong overall employee experience. A summary of these offerings, which are generally available to active, non-temporary, full-time and part-time US employees who work at least 20 hours per week, can be found here.