Site Reliability Engineer

Site Reliability Engineer – Investment FundOur client is a specialized investment firm in New York looking to hire a Site Reliability Engineer as the second engineer on its technology team.The firm is a lean, approximately 17-person investment platform focused on micro-cap PIPE and structured equity investments. Its technology stack has been built internally and includes AI applications used daily by the investment team, an internal knowledge system, scheduled data pipelines, and infrastructure supporting the firm's trading systems.This hire will work directly with the CTO and take ownership of production reliability across the platform. This is a broad, hands-on role with no layers between engineering and the investment team.What You'll DoOwn day-to-day reliability of production applications, data pipelines, AI tools, and trading-related systemsBuild and maintain monitoring, alerting, logging, and tracing across the technology environmentMonitor scheduled data pipelines and troubleshoot late or missing data, failed dependencies, retries, and rerunsServe as the first line of technical support for the firm's trading systemsDiagnose and resolve production incidents across applications, infrastructure, data, and integrationsRead, debug, and patch production Python code when issues ariseSupport Linux-based applications, shell scripts, cron jobs, and scheduled processesOperate applications and data workflows across Azure and AWSSupport deployment, backups, database connections, performance issues, and other day-to-day cloud operationsMonitor and troubleshoot LLM-backed applications, including provider outages, rate limits, model changes, silent agent failures, and unexpected token usageAutomate recurring operational work and eliminate manual processesBuild runbooks and documentation for systems currently maintained by a small engineering teamCommunicate directly with investment, trading, operations, and senior leadership when issues ariseWhat We're Looking For4–8 years of experience in Site Reliability Engineering, Production Support, Application Support, Infrastructure Engineering, Platform Engineering, or a similar hands-on production roleStrong Linux, shell scripting, and cron experienceStrong working knowledge of Python, including the ability to read, debug, and patch an existing production codebaseExperience building monitoring, alerting, logging, or tracing capabilities, rather than only operating within an established environmentHands-on responsibility for scheduled data pipelines and their day-to-day reliabilityExperience troubleshooting dependencies, retries, missing or late data, failed jobs, and pipeline rerunsExperience operating applications and data workflows in a cloud environment such as Azure, AWS, or GCPExperience running an LLM-backed application in production and troubleshooting the operational issues unique to LLM-based systemsMeaningful on-call or incident-response experience with the ability to independently own an issue from detection through resolution and postmortemComfortable operating independently within a small technology teamNice to HaveExperience at a fintech or AI product company, proprietary trading firm, broker-dealer, hedge fund, or other financial-services organizationFamiliarity with Microsoft Graph API, Entra app registrations, Teams bots, SharePoint permissions, or the broader Microsoft 365 ecosystemUnderstanding of trading systems, market data, OMS/EMS workflows, end-of-day processes, settlement, or Bloomberg/vendor dataFIX familiarityC++ exposureWho This Role Is ForThis is a strong opportunity for an engineer who enjoys owning production systems rather than working on one narrow piece of a large infrastructure organization.The ideal candidate has been the person on call, has diagnosed real production incidents, has kept scheduled pipelines running, and is comfortable figuring out whether an issue sits in the application, infrastructure, data, or upstream dependency.You'll join a very small technology team, work directly with the CTO, and have broad exposure to AI applications, data infrastructure, trading technology, and the day-to-day operations of an investment firm.There is also an opportunity for the role to evolve toward broader Software Engineering or AI Engineering responsibilities as the technology team grows.