Senior Compute Systems Engineer

SUMMARY:
A well-established business is seeking to appoint a Senior Compute Systems Engineer

POSITION INFO:
Qualifications:

• BTech in Computer Science, Software Engineering, Information Systems, Electronic Engineering or equivalent qualifications coupled with 13 years experience OR
• BENG/MTech in Computer Science, Software Engineering, Information Systems, Electronic Engineering or equivalent qualifications coupled with 9 years experience
• MENG in Computer Science, Software Engineering, Information Systems, Electronic Engineering or equivalent qualifications coupled with 7 years experience,
• PHD in Computer Science, Software Engineering, Information Systems, Electronic Engineering or equivalent qualifications coupled with 5 years experience.

• 3+ years in a technical leadership or software/system architectural role with direct responsibility for large-/platform-scale distributed systems.
• Demonstrated hands-on experience in infrastructure design and automation, distributed systems, observability, CI/CD, container orchestration (e.g. Kubernetes), DevOps/SRE practices and cloud-native technologies.
• Experience leading teams or initiatives that intersect with data platforms, storage, networking, and systems engineering domains

• In-depth understanding of systems engineering principles, including performance optimisation, fault tolerance, and resource scheduling in Linux-based environments.
• Strong knowledge of containerised environments (Docker, Podman), orchestration platforms (Kubernetes, Helm), and runtime architectures (containerd, CRI).
• Expertise in infrastructure-as-code, continuous integration/deployment (CI/CD), and configuration management tools (e.g., GitLab CI,Ansible, Terraform, ArgoCD).
• Advanced understanding of distributed computing and storage architectures, including Ceph, S3, NFS, and local/clustered file systems.
• Operational and architectural fluency in relational and NoSQL database systems (e.g., PostgreSQL, MySQL, MongoDB), including replication, backups, and performance tuning.
• Working knowledge of networking fundamentals, security protocols, and systems-level observability (e.g., Prometheus, Grafana, ELK/EFK stack).
• Familiarity with the HPC ecosystem (e.g., SLURM, job schedulers) is beneficial for environments supporting scientific or research computing.