10451 Clay Road
Houston, United States

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.
• Apply and share knowledge of HPC software development techniques, including compilers, languages, and programming models, and help support junior engineers.
• Image & instance lifecycle — build and pin machine images (Packer/AMI) and manage EC2 launch templates for rolling host and fleet replacements.

Required Qualfiications:

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field — or equivalent practical experience.
• 3–5 years of experience in DevOps, Cloud Engineering, Site Reliability Engineering (SRE), HPC, or a related technical role.
• Hands-on Linux administration in production environments — Rocky Linux 8 / RHEL — with strong shell/Bash scripting.
• Hands-on experience with an HPC workload scheduler such as Slurm (or equivalent, e.g. PBS/LSF/Grid Engine).
• Hands-on cloud experience is critical — experience with a major public cloud is required, with AWS strongly preferred (Azure or GCP considered).
• Configuration management with Ansible.
• Container technologies and orchestration — Kubernetes plus a container runtime (e.g. Docker/Podman/containerd).
• Building and maintaining CI/CD pipelines (GitLab CI or similar, e.g. GitHub Actions/Jenkins).
• Infrastructure-as-code with Terraform.
• Strong troubleshooting, analytical, and problem-solving skills, with the ability to work independently on well-defined problems and ask the right questions on ambiguous ones.
• Good communication, collaboration, and documentation skills.
• Willingness and availability to participate in a shared on-call/escalation rotation.

Preferred Qualifications:

• 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.

What Success Looks Like (Level II Expectations)

• Scope — contributes to larger projects as a technical project member and takes ownership of well-defined pieces of work.
• Managing & planning — plans, coordinates, and completes own tasks with growing independence while clearly reporting progress.
• Complexity & innovation — analyzes and diagnoses technical issues thoroughly, and optimizes existing technology while recommending improvements to procedures and methods.
• Mentoring & communication — shares knowledge and supports others, translating technical information for varied audiences.
• Internal/external focus — liaises constructively with internal and external stakeholders to understand technical and business requirements.