Senior Engineer, Advanced Computing - HPC/Kubernetes

A leading global investment firm is seeking a highly skilled and innovative Senior Infrastructure Engineer to join its elite technology team. This role offers the opportunity to work on cutting-edge infrastructure projects that directly support quantitative research and trading strategies. The ideal candidate will be passionate about high-performance computing (HPC), cloud-native technologies, and building scalable, resilient systems across hybrid environments.

Key Responsibilities
As a Senior Infrastructure Engineer, you will play a pivotal role in designing, building, and maintaining the firm's next-generation compute and storage platforms.

Your responsibilities will include:

• HPC Platform Development: Architect and enhance a high-performance computing environment tailored for research workloads, ensuring optimal performance and scalability.
• Global Storage Systems: Design, implement, and manage a robust, distributed storage infrastructure across multiple data centers and cloud environments.
• Linux Systems Engineering: Maintain and optimize a large fleet of Linux servers, focusing on performance tuning, kernel-level debugging, and system reliability.
• Kubernetes Operations: Build and support a hybrid Kubernetes estate, spanning both on-premises and AWS environments, with a focus on automation, observability, and resilience.
• Task Scheduling Infrastructure: Contribute to the development and refinement of a proprietary task scheduling system that orchestrates complex compute workflows across the firm's infrastructure.

Curiosity & Passion:

• A deep interest in emerging technologies and a commitment to continuous learning.
• Team-Oriented Mindset: Excellent communication skills and a collaborative approach to problem-solving.
• Creative Engineering: The ability to design elegant, original solutions to complex technical challenges, rather than relying solely on existing tools or frameworks.
• Automation-First Philosophy: A strong belief in infrastructure-as-code and the automation of all aspects of system management.

Required Technical Expertise
To be successful in this role, candidates should bring a strong foundation in systems engineering and software development, including:

• Linux Mastery: Deep expertise in Linux internals, including kernel operations, performance tuning, and advanced troubleshooting.
• Software & Systems Design: Proven experience designing and implementing complex systems at scale.
• Programming Proficiency: Strong coding skills in at least one compiled language (C++ or Go preferred) and one interpreted language (such as Python, Ruby, or Perl).
• Kubernetes Architecture: In-depth knowledge of Kubernetes internals, including custom operators, advanced deployment strategies, and performance optimization.
• Low-Level Debugging: Ability to diagnose and resolve intricate system-level issues using methodical analysis and creative thinking.
• AI/ML Infrastructure: Familiarity with the infrastructure demands of machine learning workloads, including GPU scheduling, data pipelines, and model training environments.
• HPC Experience: Hands-on experience with modern HPC environments, including workload orchestration, parallel computing, and performance engineering.

Preferred Qualifications (Bonus Points)

• Enterprise Storage Systems:Experience with high-performance and parallel file systems such as Vast Data, Weka, NetApp, Pure Storage, Lustre, or GPFS.
• Infrastructure as Code: Proficiency with tools like Terraform, Ansible, or Puppet for managing infrastructure declaratively.
• Observability & Monitoring: Familiarity with observability stacks such as Prometheus, Grafana, and related tools for system monitoring and alerting.
• Networking Expertise: Solid understanding of networking protocols and the ability to troubleshoot issues in distributed systems.
• Advanced I/O Hardware: Experience configuring and optimizing systems with high-performance I/O hardware, including NVMe, RDMA, and specialized interconnects.