Balyasny Asset Management (BAM) is a diversified global investment firm founded in 2001 by Dmitry Balyasny, Scott Schroeder, and Taylor O'Malley. With over $32 billion in assets under management, BAM employs more than 2,000 people across 23 offices in the U.S. and Canada, Europe, the Middle East, and Asia. The firm’s investment teams span five strategies, including Equities Long/Short, Fixed Income & Macro, Commodities, Multi-Asset Arbitrage, and Systematic. Balyasny’s mission is to deliver to its investors absolute, uncorrelated returns in all market environments.
We are seeking a Trading Platform Engineer to join our Systematic Technology team, focused on the reliability, observability, and day-to-day support of a high-performance, low-latency trading platform.
This role is primarily centered on production engineering and trading support. The ideal candidate will have experience supporting business-critical, real-time systems in production, with strong skills in monitoring, incident response, troubleshooting, automation, system behavior analysis, and operational control. They will work closely with trading, Quantitative Researchers, and developers to ensure the platform is stable, well monitored, and responsive to front-office needs.
Key Responsibilities
- Provide production support for a high-performance, low-latency trading platform in a live trading environment.
- Monitor system health, trading workflows, and platform behavior to ensure reliability and rapid issue detection.
- Respond to production incidents, drive triage and resolution, and coordinate effectively across trading, development, and infrastructure teams.
- Support front-office users by investigating trading issues, answering workflow questions, and helping resolve time-sensitive production problems.
- Own and improve monitoring, alerting, telemetry, and operational dashboards across the trading platform.
- Develop and enhance automation, runbooks, and operational tools to improve supportability and reduce operational risk.
- Perform root cause analysis on production issues and drive follow-up actions to improve platform resilience.
- Support release processes, change management, and controlled production rollouts.
- Monitor and investigate data quality, platform behavior, and workflow exceptions across trading and market data processes.
- Partner with engineering teams to improve recoverability, observability, and operational readiness of trading applications.
- Help define and maintain operational standards, support procedures, and production controls.
Required Qualifications
- Strong experience in production engineering, SRE, or application support within real-time or trading environments.
- Experience supporting business-critical production systems with a strong sense of urgency and ownership.
- Strong understanding of monitoring, observability, alerting, incident management, and root cause analysis.
- Experience supporting front-office users in a fast-paced environment.
- Strong troubleshooting skills across application and system behavior in a Linux environment
- Strong attention to detail, operational discipline, and focus on platform stability.
- Ability to work effectively with trading, Quantitative Researchers, and software engineering teams.
- Scripting or automation experience in Python or similar.
Preferred Qualifications
- Experience supporting systematic trading, electronic trading, or market data platforms.
- Familiarity with order lifecycle, execution workflows, and trading controls.
- Experience with telemetry platforms, logging, metrics, and production diagnostics.
- Exposure to low-latency environments and real-time operational support.
- Proficiency in SQL and databases
Success in the Role
Success in this role will require:
- Strong ownership of production reliability and front-office support
- A disciplined approach to incident response, monitoring, and operational control
- The ability to troubleshoot quickly and communicate clearly under pressure
- Strong partnership with trading, research, and engineering teams
- A continuous focus on improving observability, stability, and support processes