System Software Engineer

Position Overview

We are seeking a System Software Engineer to help build, deploy, and operate a modern multi-cloud computational platform and model-serving infrastructure supporting advanced AI/ML applications. This role focuses on implementation, automation, and the day-to-day operation of production systems while working alongside senior engineers within an established cloud platform architecture.

The successful candidate will deliver reliable, well-tested infrastructure changes while expanding expertise in Kubernetes, GPU-enabled workloads, observability, and continuous delivery in a production environment.

This position offers the opportunity to grow in cloud infrastructure, distributed systems, and machine learning operations through hands-on experience with production systems, mentorship from experienced engineers, and increasing technical ownership over time.

Key Responsibilities

• Implement and maintain Kubernetes workloads and supporting resources, including manifests, Helm charts, controllers, networking, ingress, and storage configurations.
• Deploy and operate GPU-accelerated model-serving workloads, including autoscaling, resource allocation, and environment-specific deployment configurations.
• Support distributed GPU training and simulation workloads.
• Build and maintain observability solutions using Prometheus, Grafana, and OpenTelemetry, including dashboards, alerting, metrics, and tracing.
• Develop and enhance CI/CD pipelines to automate build, test, and deployment processes while supporting progressive delivery practices.
• Create and maintain infrastructure-as-code modules and automation scripts to support consistent, repeatable cloud infrastructure deployments.
• Participate in production incident response, execute operational runbooks, and contribute to root cause analysis and remediation efforts.
• Troubleshoot issues across infrastructure components, including containers, Kubernetes clusters, networking, compute nodes, and GPU resources.
• Produce clear technical documentation, including runbooks, implementation guides, and design documentation.
• Participate in code reviews and technical design discussions, incorporating feedback to improve solution quality.

Required Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related field, plus three (3) years of relevant experience; or an equivalent combination of education and experience.
• Experience supporting production cloud infrastructure, DevOps, Site Reliability Engineering (SRE), or backend platform environments.
• Working knowledge of Kubernetes, including deploying, managing, and troubleshooting production workloads.
• Experience with at least one major cloud platform such as AWS, Google Cloud Platform (GCP), OpenStack, or similar.
• Experience with observability tools, including Prometheus, Grafana, OpenTelemetry, or comparable monitoring and tracing platforms.
• Familiarity with CI/CD tools and automated software delivery pipelines.
• Experience with infrastructure-as-code and configuration management tools such as Helm, Ansible, Puppet, Terraform, or similar.
• Proficiency in at least one scripting or programming language used for infrastructure automation (Python, Go, Rust, Bash, or equivalent).
• Comfortable working in Linux environments and using Git-based development workflows.

Preferred Qualifications

• Experience supporting GPU-accelerated or AI/ML workloads.
• Exposure to multi-cloud environments.
• Familiarity with model-serving frameworks such as vLLM, NVIDIA Triton, or similar technologies.
• Experience compiling, packaging, and configuring Linux software.
• Experience with high-performance computing (HPC), batch schedulers, or MPI-based workloads.