Ansatz Capital

Quantitative trading software firm, research-driven

Software Engineer

Backend EngineeringConfirmed live in the last 24 hours

Full-timeNew York, NY, USAHybrid

About the Job

Requirements

C++11 and higher experience
Excellent design and debugging skills
Experience developing for production critical systems
Excellent communication and prioritization skills

Responsibilities

Develop and maintain scalable trading applications and infrastructure for many financial markets
Assist with developing the full stack of infrastructure to support trading operations
Work in a fast-paced environment with daily or more frequent release cycles and prioritize between longer and shorter term needs
Optimize latency and bandwidth across hardware drivers, TCP/multicast handlers, and Python interfaces; understand trade-offs in clock cycles and CPU cache effects
Use multi-core/multi-threaded communications with lock-free algorithms to maximize computational throughput; understand run-time behavior, serialization delays, and asymptotic behavior in this environment

Desired Qualifications

Experience with Python
Experience with x86 hardware
Experience with performance engineering
Understanding of Intel Xeon pipelining and cache behavior
Experience with the TCP networking stack
Experience optimizing Linux kernels / using kernel-bypass networking
Experience leveraging AWS or similar cloud infrastructure

We are looking for a software engineer to join a lean and technical quantitative trading startup. You’ll be responsible for developing and maintaining scalable trading applications and infrastructure for many financial markets and assist with developing the full stack of infrastructure to support trading operations. The role is fast paced, with daily or even more frequent release cycles, and requires a good sense of prioritization between longer and shorter term needs.

Within our systems, from hardware drivers to TCP/multicast handlers to Python interfaces, each layer requires custom optimization for latency, bandwidth, or both. An understanding of trade-offs in terms of clock cycles and CPU cache effects is a must. Multi-core/multi-threaded communications using lock-free algorithms will be employed to increase the theoretical computational limit per unit time; consequently, the candidate should have a good grasp of run-time behavior, serialization delays, and asymptotic behavior in this environment. Compensation consists of base salary, discretionary performance bonus, and possible participation in longer-term incentive schemes.

Skill Requirements

C++11 and higher experience
Excellent design and debugging skills
Experience developing for production critical systems
Excellent communication and prioritization skills

Technical Details About Us

Linux shop running modern kernels
C++20 codebase, Python layer on top
Technical expertise throughout (everyone programs)
Cloud-scalable research infrastructure

Desirable Skills

Experience with Python
Experience with x86 hardware
Experience with performance engineering
Understanding of Intel Xeon pipelining and cache behavior
Experience with the TCP networking stack
Experience optimizing Linux kernels / using kernel-bypass networking
Experience leveraging AWS or similar cloud infrastructure

Benefits

Catered meals and bountiful snacks
Generous budget for home office equipment
Health / Dental / Vision / 401k
Fitness and wellness benefits
Base compensation: $150,000-250,000 with additional discretionary annual performance bonus

About the Company

Ansatz Capital

Quantitative trading software firm, research-driven

Ansatz Capital is a quantitative trading software firm that builds and uses software and a research framework to study and implement trading strategies. The company treats markets as an intellectual discipline, with a lean, collaborative team supported by a high-end technology stack to generate and test research ideas and quickly turn them into trading implementations. Its approach centers on strong teamwork and rapid idea execution, aiming to produce practical, well-researched strategies rather than rely on large, slow organizational structures. The goal is to develop and apply quantitative methods that generate actionable trading ideas and turn them into profitable trades efficiently.

Company size: 11-50
Company stage: Not listed
Total funding: Not listed
Headquarters: New York City, New York
Founded: 2013

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