System Operations Engineer

Key Responsibilities

• Utilize Microsoft Intune and Entra ID to manage device lifecycles, configuration profiles, and user identities. Ensure workstations are compliant, secure, and optimized for trading and administrative functions.
• Use functional programming principles (e.g., with PowerShell) to build modular, idempotent, and reusable automation for user provisioning and software deployments.
• Use REST APIs to connect infrastructure tools, automate data pulls, and streamline workflows between different platforms.
• Provide technical support for data center operations, including racking/stacking and using LOM tools like iDRAC or iLO for remote server administration.
• Support the hardware and software environments required for AI and Machine Learning workloads, including high-spec GPU workstations and server configurations.
• Conduct system testing to identify inefficiencies in hardware (CPU/GPU/Memory) and software deployments to maintain a low-latency edge.
• Maintain rigorous documentation for trading applications, exchange connectivity, and internal SOPs.

Qualifications

• 3–5 years in System Operations, Systems Engineering, Desktop Engineering or a high-pressure Technical Support role.
• Strong proficiency in Windows (10/11 & Server).
• Practical experience with Microsoft Intune and a solid understanding of Entra ID (Azure AD). Understanding of Active Directory.
• Proficiency in a functional programming style; ability to write clean, logic-driven, and testable code.
• Experience using REST APIs to interact with web services or automate system tasks.
• Deep knowledge of PC/Server components (GPUs, RAM types, CPU architectures) and familiarity with Data Center environments.
• Excellent troubleshooting skills with the ability to dig through system log files to identify root causes.
• Ability to make sound, rapid decisions in a fast-paced trading environment.
• Work with AI based tools, checking to ensure that they are doing what they are supposed to. Avoiding pitfalls of just trusting what the machine says.

Nice-to-Haves

• Familiarity with Linux (RHEL/Ubuntu/CentOS) administration.
• Awareness of the infrastructure requirements for supporting internal AI models or LLMs.
• Comfort performing occasional physical work, including equipment moves and data center cable management.

Compensation

Base Salary Range: $75,000 - $90,000, plus eligibility for a performance-based bonus.