A technology-focused investment organization is seeking a Senior Cloud Platform Engineer to help develop and operate reliable, secure infrastructure across AWS, Azure, and hybrid computing environments.
The position is a hands-on individual contributor opportunity focused on Terraform-based infrastructure automation, shared engineering standards, cloud identity, networking, and production operations. The engineer will work closely with architects, infrastructure teams, and security stakeholders to improve how technical teams provision and operate cloud environments.
RESPONSIBILITIES- Engineer reusable Terraform infrastructure modules and automated cloud deployment patterns.
- Develop standardized AWS and Azure environments with built-in security and governance controls.
- Design and support hybrid networking and private connectivity between cloud and on-premises systems.
- Implement cloud identity, access controls, and secure workload authentication.
- Build infrastructure CI/CD pipelines and automate deployment validation.
- Take infrastructure projects through design, implementation, testing, and production.
- Troubleshoot complex infrastructure failures and contribute to root-cause analysis.
- Improve infrastructure monitoring, operational documentation, security, and reliability.
Role Requirements- 5+ years of production cloud infrastructure engineering experience.
- Strong AWS or Azure infrastructure engineering experience, with practical experience in the other platform.
- Proven experience building reusable Terraform modules for other teams.
- Strong networking and hybrid connectivity skills.
- Practical AWS and Azure identity and access management experience.
- Infrastructure CI/CD and deployment automation experience.
- Hands-on production troubleshooting and incident-response experience.
- Demonstrated ownership of infrastructure projects through production.
- Strong cloud security, change-management, and documentation practices.
PREFERRED EXPERIENCE- Experience with GPU/HPC or infrastructure supporting AI and machine learning workloads.
- Kubernetes infrastructure experience.
- Internal developer platform or self-service infrastructure engineering.
- Infrastructure testing, policy automation, and scripting.
- Data-platform infrastructure or regulated computing environments.