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Senior Cloud Infrastructure Engineer

Catch Talent

Senior Cloud Infrastructure Engineer

A top-tier quantitative trading firm is hiring a Senior Cloud Infrastructure Engineer to design and own the high-performance compute platform powering some of the world's most sophisticated trading strategies. This is a rare opportunity to architect cutting-edge cloud infrastructure at a firm with a 25+ year track record of innovation, where your work will have a direct, measurable impact on trading performance and engineering excellence.

This firm is a leading quantitative trading company with over two decades of innovation and a global footprint spanning more than a dozen offices worldwide. The organization is home to some of the world's best systematic trading and engineering talent, operating a high-performance platform built for scale, speed, and reliability. Engineers thrive here while solving challenging problems in low-latency programming, FPGA technology, hardware acceleration, and machine learning. The firm's ongoing investment in top talent and technology ensures its platform remains unmatched in functionality, scalability, and performance.

Why You'll Love This Role

  • Work for a stable, high-growth organization that actively supports personal and professional development.
  • Leverage deep expertise in cloud infrastructure, HPC, and distributed systems in ways that directly shape trading performance and platform capability.
  • Solve genuinely hard technical problems in low-latency infrastructure, Kubernetes, and large-scale cloud migrations alongside world-class engineers.
  • Enjoy a stimulating, results-oriented environment with a collaborative culture, no egos, and a team that celebrates great ideas.

What You'll Do

  • Architect and implement scalable cloud infrastructure using Terraform or equivalent Infrastructure-as-Code tools.
  • Design high-performance compute environments, including optimized networking and storage stacks.
  • Manage and optimize Kubernetes clusters in cloud environments.
  • Automate infrastructure workflows and build complex CI/CD pipelines.
  • Build and maintain custom cloud images.
  • Implement robust monitoring and observability for performance-critical workloads.
  • Lead on-prem to cloud and cloud-to-cloud migrations of HPC and distributed workloads.
  • Collaborate with research and engineering teams to optimize compute, storage, and scheduling efficiency.

What You Bring

  • A bachelor's degree in Computer Science or a related field.
  • At least 5 years of relevant experience in cloud infrastructure or related engineering roles.
  • Proficiency in Bash, Python, or Go for automation.
  • Strong expertise in HPC and distributed workloads to design scalable, high-performance cloud infrastructure.
  • Deep hands-on experience with Infrastructure as Code, Linux systems, cloud networking, and storage architectures.
  • Ability to build automated, production-grade cloud platforms for compute-intensive environments.
  • Deep understanding of cloud networking, storage architectures, and storage protocols (NFS, object, block, parallel/distributed storage).
  • Expertise with Terraform or equivalent IaC tools.
  • Experience with HPC schedulers such as Slurm or HTCondor.
  • Experience with distributed computing frameworks such as Ray.
  • Eligibility to work in the US for any employer (sponsorship is not available).

Compensation and Perks

  • Base salary, plus eligibility for a discretionary bonus.
  • Generous paid time off policies.
  • Savings plans and other financial wellness tools.
  • Hybrid working opportunities from the firm's NYC headquarters in the Financial District.
  • Free breakfast, lunch, and snacks daily.
  • In-office wellness experiences and reimbursement for select wellness expenses (gym, personal training, and more).
  • Company-sponsored sports teams and fitness events.
  • Volunteer opportunities and charitable giving.
  • Social events, happy hours, and celebrations throughout the year.
  • Workshops and continuous learning opportunities.
Vacancy posted 1 day ago
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