Production Support Engineer

Production Support Engineer

NYC based financial firm is seeking a technically curious support engineer to join their Front Office Technology team. Responsibilities and Impact: Build and automate Design and build Python-based tooling to automate recurring operational checks, reducing manual intervention and improving system observability Develop and maintain Grafana dashboards and alerting infrastructure to shift the team from reactive troubleshooting to proactive detection Contribute to companies AI capabilities in an operational context -- including AI-assisted alert triage and anomaly detection as our platform matures Identify repeating failure patterns and engineer permanent solutions rather than recurring workarounds Maintain clear, high-quality documentation of systems, workflows, and runbooks -- with a bias toward making documentation redundant through automation Operate and support Monitor and maintain the health of their technology platform and related trading applications throughout the trading day Respond to and resolve production incidents across trading systems, managing communications with investment, risk, and operations teams Perform QA testing for new functionality ahead of release Liaise with external brokers and vendors on order flow and market data issues Collaborate with development teams to escalate and resolve complex technical problems Build and maintain relationships with business stakeholders across investment and middle office teams Required skills: Bachelor's degree in an IT related discipline 3-5 years of experience in a production or application support function, ideally within financial services or a trading environment Strong Python skills -- you write tooling, not just scripts Working knowledge of FIX protocol, Linux, and SQL Server Experience with observability or monitoring tools (Grafana, or similar) Familiarity with trading or execution systems (EMSX, Flextrade, or similar EMS) Exposure to market data platforms, Git, and Jira Curiosity about AI/LLM tooling and how it can be applied in an operational context The resilience to operate under pressure during market hours, and the drive to make those moments rarer over time

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