Overview
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:
o Consensus
o Replication
o Fault tolerance
o CAP theorem tradeoffs
* Experience with
o Python or similar programming languages
o Infrastructure as Code (Terraform, Ansible)
o Container runtimes (containerd, CRI-O)
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