Job Description

We are seeking a highly technical Senior Platform Engineer with deep expertise in Linux Engineering, OpenStack development, Kubernetes, and GPU-enabled infrastructure to design, build, and operate SIG’s next-generation infrastructure platforms supporting trading and core technology environments.

• This is a hands-on engineering role focused on building and tuning scalable, resilient, and high-performance infrastructure systems across CPU and GPU workloads. The ideal candidate will have strong Linux internals knowledge, experience developing and operating cloud-native platforms, and a deep understanding of distributed systems architecture, including the efficient provisioning, isolation, and performance tuning of accelerator-based compute resources.

What we’re looking for

Linux Systems Engineering

• Deep troubleshooting across kernel, networking stack, storage, and performance layers.
• Performance tuning for low-latency systems (CPU pinning, NUMA, IRQ balancing, kernel tuning).
• Develop automation using Python, Go, or similar languages.
• Build and maintain infrastructure tooling and internal platform services.
• Implement high-availability solutions and disaster recovery strategies.
• Perform root cause analysis for production incidents affecting distributed systems.
• Design, deploy, and operate GPU-enabled infrastructure. Optimize GPU utilization (memory bandwidth, PCIe throughput, multi-process service, MIG partitioning where applicable).
• Tune workloads to efficiently leverage NVIDIA GPUs (or equivalent accelerators) for compute-intensive applications.
• Troubleshoot GPU driver, CUDA, kernel module, and firmware-related issues in production environments.

OpenStack Development & Cloud Infrastructure

• Develop and extend OpenStack services (Nova, Neutron, Cinder, Keystone, etc.).
• Build custom integrations and automation around OpenStack APIs.
• Optimize compute, networking, and storage performance for high-performance workloads.
• Design multi-tenant OpenStack architectures with strong isolation and security.
• Contribute to infrastructure-as-code frameworks managing OpenStack environments.
• Debug and resolve deep issues across hypervisors (KVM), networking layers, and control plane services.
• Integrate OpenStack environments with Kubernetes platforms (hybrid cloud architectures).

Kubernetes Platform Engineering

• Design, build, and operate highly available, production-grade Kubernetes clusters.
• Develop and maintain Kubernetes operators, controllers, and custom resource definitions (CRDs).
• Implement advanced scheduling, multi-tenancy, and workload isolation strategies.
• Optimize cluster performance for low-latency and high-throughput workloads.
• Integrate Kubernetes with CI/CD pipelines and GitOps workflows.
• Implement cluster observability using Prometheus, Grafana, OpenTelemetry, etc.
• Design and enforce networking policies (CNI), ingress architecture.
• Implement secure cluster design including RBAC, OPA/Gatekeeper, secrets management, and runtime security.

Automation & Infrastructure as Code

• Design and maintain infrastructure using Terraform, Ansible, Helm, or similar tools.
• Build CI/CD pipelines for infrastructure and platform deployments.
• Implement immutable infrastructure and GitOps methodologies.
• Create automated validation, testing, and deployment frameworks for platform services.

Required Technical Skills

• Advanced Linux systems knowledge (kernel, networking, storage)
• Experience deploying and operating GPU-enabled Linux servers
• Understanding of CUDA drivers, GPU kernel modules
• Performance profiling and Tuning Workloads for compute-intensive applications.
• Hands-on OpenStack development and operations experience
• Strong experience administering and engineering production Kubernetes clusters
• Strong understanding of distributed systems principles:
  • Consensus
  • Replication
  • Fault tolerance
  • CAP theorem tradeoffs
• Experience with
  • Python or similar programming languages
  • Infrastructure as Code (Terraform, Ansible)
  • Container runtimes (containerd, CRI-O)
  • Observability stacks (Prometheus, Grafana, ELK)

Desirable Experience

• Experience in low-latency or high-performance trading environments
• High-performance networking (DPDK, SR-IOV, CNI tuning)
• Storage systems (Ceph, distributed storage, NVMe optimization)
• Contribution to open-source projects (Kubernetes, OpenStack)
• Experience designing multi-region or hybrid cloud architectures
• Experience tuning AI/ML, quantitative, or high-performance compute workloads on GPUs
• Experience with NVIDIA DCGM, MIG (Multi-Instance GPU), or vGPU configurations
• Familiarity with RDMA, GPUDirect, or high-throughput interconnects
• Experience optimizing containerized ML or compute pipelines

Key Attributes

• Strong systems thinking and deep technical curiosity
• Ability to diagnose complex cross-layer failures
• Passion for building reliable, scalable distributed systems
• Comfortable operating in high-availability, high-performance production environments
• Strong documentation and knowledge-sharing mindset