Senior Software Engineer, Execution Engineering

Overview

Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future.

Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. The people who shape our company come from other backgrounds, including concert music performances, humanitarian aid, opera singing, sports writing, and BMX racing. You will be part of a team that loves to succeed together.

In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more.

As a Senior Software Engineer on our Execution Engineering team, you will be developing the company s production trading systems and the data pipelines that drive our machine learning in both production and research. You will be expected to work closely with both our traders and research teams to contribute to a platform that supports a diverse set of requirements and complex trading behaviors.

We look for brilliant people with a passion for solving problems through innovation and engineering fundamentals. You’ll work in a collaborative environment that encourages creative thinking and efficient implementation. We embrace experimentation. You’ll work alongside experienced engineers recruited from leading technology companies and universities. You and your team will collaborate closely with top machine learning researchers.

• Design real-time distributed trading systems that place orders across a global set of markets and asset classes
• Integrate with new assets and markets and drive clarity on the resulting requirements
• Take ownership of entire outcomes, and continue to support and grow them through iteration, documentation, and testing
• Own observability and remediation tooling used to analyze trading performance and risk
• Improve the resilience and performance of our trading systems
• Participate in on-call rotations and drive incident response, root-cause analysis, and postmortems
• Lead projects spanning a number of engineering teams and collaborate with non engineering stakeholders
• Mentor and develop other engineers on the team, and share your practices and knowledge with the team and company

• Bachelor’s, Master’s, or Doctoret degree in Computer Science, Engineering, or a related field (or equivalent experience)
• 5+ years of software engineering experience architecting and operationalizing high-performance, scalable, reliable, and resilient distributed systems
• Proven expertise in building cloud-native, distributed systems on any one of AWS, Azure, or GCP
• Demonstrated experience with modern cloud technologies and data observability tools (e.g., Cloud Watch, Grafana, Prometheus), and Infrastructure-as-Code (e.g., Cloud Formation, Terraform)
• Experience designing telemetry standards (structured logs, metrics, distributed traces) and building dashboards and actionable alerting
• Comfortable working in a containerized environment with Docker, Kubernetes, etc
• Strong coding, analytical, debugging, and troubleshooting skills including use of industry standard tools
• Great at communicating and influencing stakeholders

• Familiarity with the trading domain; experience in trading/execution systems (Order Management Systems, market data, order lifecycle)
• Demonstrated ability to leverage AI tools to enhance productivity, streamline workflows, and support decision-making
• Track record mentoring engineers and leading technical direction

The base salary range for this position is $225,000 to $255,000 in the location(s) of this posting. Individual salaries are determined through a variety of factors, including, but not limited to, education, experience, knowledge, skills, and geography. Base salary…