Systems Engineer
Aquatic Capital Management
| Company | Aquatic Capital Management |
| Category | Engineering |
| Location | Chicago |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 8 May 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
Aquatic was founded with a shared passion for tackling some of the most complex challenges in one of the world’s most competitive arenas—global financial markets. From the very beginning, we have been driven by a deep commitment to applying cutting-edge scientific research and technological innovation to deliver unparalleled performance. Our journey is one of continuous growth and exploration, marked by a spirit of curiosity and relentless drive for excellence. Aquatic Capital Management is seeking a Systems Engineer to join our team.
Systems Engineer
Infrastructure & Research Computing
Aquatic Capital Management • Chicago, IL • Full-Time
About the Role
We are hiring a Systems Engineer to join our Infrastructure team. This is a senior individual contributor role with significant architectural ownership, and real accountability for how our research and trading systems compute.
You will own and evolve the compute infrastructure that powers quantitative research and production trading at Aquatic: our on-premise grid, hybrid cloud compute (GCP and AWS), GPU workloads, storage systems, and the automation that ties it all together.
What You Will Do
Grid & High-Performance Computing
Own and evolve Aquatic's Slurm and Ray cluster infrastructure across on-prem and GCP — supporting research and trading workloads including fitting, tuning, backtesting, feature computation, and market data processing.
Drive architectural improvements to capacity, scheduling efficiency, and throughput across the full footprint, including GPU computation.
Design and maintain the connectivity and automation between on-prem and cloud environments
Evaluate and implement newer compute paradigms as research needs evolve
Storage & Performance
Own high-performance storage systems including VAST (NFS and S3-compatible), ensuring data access is fast and reliable across research, trading, and build workloads.
Investigate and resolve performance bottlenecks at the intersection of storage, network, and compute.
Developer Experience & Automation
Design and maintain provisioning systems for complex compute resources and datacenter onboarding.
Own and improve CI/CD infrastructure (GitHub Actions) as well as the development toolchain for the broader engineering organization.
Technical Leadership & Mentorship
Serve as the go-to architect for infrastructure decisions; provide technical direction and help establish vision across the team.
Pair with and mentor earlier-career Systems & Software Engineers, helping them develop sound instincts and grow their skills.
Diagnose and resolve the hardest, most obscure system issues that others cannot get to the bottom of.
What We Are Looking For
Required
10+ years of experience in systems engineering, infrastructure, or a closely related discipline.
Deep Unix/Linux expertise across multiple distributions; comfortable at every layer of the stack.
Strong experience with HPC grid systems (SLURM preferred) in a research or scientific computing environment.
Experience provisioning and managing bare-metal infrastructure and data centers, not just cloud-native environments.
Familiarity with high-performance / parallel storage systems (VAST, GPFS, Lustre, or similar).
Strong scripting and automation fluency (Bash, Python, or similar); able to build tools that others rely on and to contribute to and own production codebases.
Ability to operate as an independent technical leader: establishing direction, building trusted relationships, and communicating clearly with stakeholders outside the team.
Strongly Preferred
Experience with distributed compute frameworks such as Ray, Dask, or Spark in a research context.
Low-level systems programming on Linux using C/C++, with a focus on performance and reliability.
Experience with GPU computation and instru
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