Cgg
HPC DC Lead Solution Architect
Houston, United States of America · Senior
Sponsorship not specifiedDetected 20 days ago
PythonBashCloud PlatformsKubernetesLinuxStakeholder ManagementResearchLeadershipCommunicationProblem SolvingMentoring
About the role
- You'll combine deep Linux/HPC expertise with strong stakeholder engagement and execution skills, translating business needs into robust technical solutions.
- As a recognized SME, you'll advise senior leadership and engage directly with clients on key architecture decisions.
Responsibilities
- Own end-to-end architecture and delivery of HPC and cloud infrastructure projects
- Translate business and research needs into scalable designs and implementation roadmaps
- Drive architecture standards, design reviews, and governance across platforms
- Partner cross-functionally to deliver integrated, compliant solutions
- Lead automation and Infrastructure-as-Code initiatives to improve reliability and speed
- Provide technical leadership, mentorship, and design oversight
- Lead design reviews and ensure quality across deliverables
Requirements
- Expertise in systems architecture, automation, and Infrastructure-as-Code
- Experience with containers, cloud, and open-source technologies
Nice to have
- Bachelor's degree in a related field or equivalent experience
- Proven experience in HPC, Linux, automation, and cloud technologies
- Strong communication and customer-facing skills
- Ability to thrive in a fast-paced, global environment
- Kubernetes, OpenStack, GPU platforms, parallel file systems, cloud/virtualization, or relevant certifications
- Our Hiring Process
- Due to the high volume of applications we receive, we may not be able to provide individual feedback to every applicant.
- Only candidates whose qualifications closely match the role criteria will be contacted for an interview.
Company info
- We are seeking an experienced Lead HPC Solution Architect to join our Technical Projects Group.
This listing is sourced directly from Cgg's careers page and normalized into a canonical job model.