DevOps Engineer II
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Not specified
- Seniority
- Middle
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Devops
- Posted
Skills
Nice to have
- AWS depth — hands-on with core services (e.g., EC2, S3, VPC, IAM, EKS/ECS, CloudFormation/CDK, CloudWatch); AWS certification a plus.
- Experience with parallel/clustered filesystems (e.g., Lustre, BeeGFS, GPFS/Spectrum Scale, Panasas, or VAST) and high-speed interconnects.
- Experience supporting large-scale HPC compute/storage environments and visualization services.
- Kubernetes at scale (Helm, autoscaling, networking/ingress, namespace/resource governance).
- Depth in Python and Bash automation; Perl or PowerShell a plus.
- Observability tooling (Prometheus, Grafana, CloudWatch, ELK/OpenSearch, Splunk).
- Cloud security fundamentals: IAM least-privilege, secrets management, image scanning.
- Relevant certifications (e.g., AWS Solutions Architect Associate, CKA/CKAD, HashiCorp Terraform Associate).
- Exposure to hybrid/multi-cloud environments, cloud migration, or workload modernization.
Full description
TGS is seeking a DevOps Engineer II to help design, build, and operate the cloud and high-performance computing (HPC) infrastructure that powers our global seismic imaging and data processing. Working alongside HPC, Enterprise IT, and R&D teams, you will automate and optimize hybrid on-premise and cloud environments, help mature our containerized and Kubernetes-based platforms, and improve the reliability, security, and performance of the systems our geoscientists depend on. This is a mid-level role for an engineer who can work with growing autonomy on well-defined problems, bring sound technical judgment to ambiguous ones, and collaborate closely with senior engineers to deliver stable, scalable, and secure solutions. We are a team that actively embraces enterprise AI tooling to work smarter, and we value engineers who do the same.
Key Responsibilities:
- Contribute to the design, planning, integration, maintenance, and support of TGS's cloud and containerized architecture as part of the broader technical cloud strategy.
- Support development and execution of cloud, container, and Kubernetes implementation strategies within the existing IT and HPC infrastructure.
- Collaborate with colleagues across HPC Computing, Enterprise IT, and Upstream/Downstream business units to design and deliver HPC solutions, both on-premise and in the cloud.
- Automate, optimize, troubleshoot, and resolve system problems and business solutions effectively and efficiently.
- Ensure technical solutions align with the vision, principles, architecture, and standards defined by the relevant architecture, security, and data teams.
- Support HPC infrastructures across multiple sub-environments — visualization, compute, storage, interconnects, code, and systems management.
- Maintain system software: use debugging tools for problem isolation and perform software builds, upgrades, and patch installation as needed.
- Build and maintain CI/CD pipelines and infrastructure-as-code to support reliable, repeatable delivery across development, staging, and production.
- AI-Assisted Automation & Engineering — use enterprise-approved AI tools (e.g., Claude, Cursor, GitHub Copilot) to accelerate automation, coding, troubleshooting, and documentation, validating outputs for quality and security; apply them to eliminate recurring incidents and manual tasks, reducing toil and improving resolution times.
- Site Reliability Engineering — apply SRE practices including observability, SLI/SLOs, monitoring, logging and alerting, incident response, and root-cause analysis to continuously improve reliability and performance.
- Participate in a shared on-call rotation providing escalation support for production HPC and cloud infrastructure.