Engineer Jobs

About The Position

Requirements

• At least 5 years of experience in Site Reliability Engineering, Infrastructure Engineering, Systems Engineering, or Platform Operations.
• Strong expertise administering Linux and Unix operating systems in large-scale enterprise environments.
• Hands-on experience with HPC platforms.
• Strong experience administering and troubleshooting SLURM workload managers.
• Experience supporting Red Hat OpenShift and Kubernetes-based container platforms.
• Deep understanding of monitoring and observability platforms, including Grafana.
• Experience managing PostgreSQL databases in production environments.
• Experience supporting Redis clusters and caching technologies.
• Strong knowledge of networking, storage, security, and enterprise infrastructure concepts.
• Experience with scripting and automation using Python, Bash, or similar languages.
• Experience leading production incident response and root-cause analysis.
• Knowledge of high-availability architectures, disaster recovery, and resilience engineering practices.

Nice To Haves

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience.
• Experience supporting AI/ML, LLM, GPU, or GenAI platforms.
• Experience managing NVIDIA GPU infrastructure, GPU operators, and AI workloads.
• Familiarity with vLLM Inference Server, JupyterHub, or AI development platforms.
• Experience with Infrastructure-as-Code tools such as Ansible or Terraform.
• Experience with CI/CD pipelines and DevOps methodologies.
• Knowledge of Prometheus, Elasticsearch, Loki, or other observability technologies.
• Understanding of enterprise vulnerability management and regulatory compliance processes.
• Experience working in highly regulated financial services or large enterprise environments.
• Certifications such as Certified Kubernetes Administrator (CKA), Red Hat OpenShift Administration Certification, Google SRE Certification, Red Hat Certified Engineer (RHCE), or AWS/Azure Cloud Certifications.

Responsibilities

• Code solutions and unit test them to deliver requirements or stories according to acceptance and compliance criteria.
• Use multiple architectural components across data, application, and business domains in designing and developing client requirements.
• Perform Continuous Integration and Continuous Development (CI/CD) activities.
• Contribute to story refinement and requirements definition.
• Estimate the work required to deliver stories or requirements through the delivery lifecycle.
• Contribute to integration, regression, and performance test suites; analyze reports, identify issues or errors, and triage their underlying causes.
• Perform spikes or proofs of concept as needed to mitigate risk or implement new ideas.
• Ensure availability, reliability, scalability, and performance of AI HPC infrastructure supporting AI/ML training and inference workloads.
• Administer and optimize Linux/Unix-based HPC environments for stable, secure, and efficient operations.
• Manage and optimize SLURM workload scheduling, GPU resource allocation, queue management, and cluster utilization.
• Design, implement, and maintain observability and monitoring solutions using Grafana and related technologies.
• Support and administer OpenShift container platforms for reliable deployment and operation of AI services.
• Manage PostgreSQL and Redis environments, including performance tuning, backup and recovery, and high-availability configurations.
• Lead production incident response, root-cause analysis, and problem management to improve platform resiliency.
• Develop automation solutions, operational tooling, and Infrastructure-as-Code capabilities to improve reliability and operational efficiency.
• Perform capacity planning and performance management for GPU, compute, storage, and networking resources.

Benefits

• Benefits eligibility
• Paid time off
• Annual discretionary incentive plan