Staff Platform Engineer - Cloud Infra & DevOps Leader

Shield AI; San Diego (TX); On-site; USD 142,000 - 213,000; Full time

Benefits offered by this job

Equity

Bonus

Benefits

Job summary

Shield AI is seeking a Staff Platform Engineer to design and evolve internal platform infrastructure spanning cloud, on-prem, and hybrid environments. You will partner with engineering, security, and operations to enable secure software delivery and provide paved paths for developers.

The role emphasizes scalable architecture, automation, and observability, with close collaboration across teams to improve reliability and development productivity in a dynamic defense-tech setting.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience.
• 8+ years in platform engineering, DevOps, or SRE roles for large-scale systems.
• Hands-on with cloud/hybrid infrastructure, networking, identity, compute, and storage.
• Proficiency with Infrastructure as Code and automation (Terraform, Ansible, etc.).
• Experience building or improving CI/CD pipelines and developer tooling.

Responsibilities

• Design, build, and operate scalable internal platform infrastructure across cloud, private cloud, and on‑prem environments.
• Develop repeatable, secure deployment patterns and infrastructure-as-code modules.
• Advance CI/CD pipelines, observability, and developer tooling to boost productivity.
• Collaborate with security and engineering teams to embed controls and meet compliance needs.

Skills

Platform engineering

CI/CD automation

Cloud & on-prem

Python

Education

Bachelor's degree in CS or related field

Tools

Terraform

Ansible

Kubernetes

CI/CD pipelines tooling

Job description

Shield AI is seeking a Staff Platform Engineer to design and evolve internal platform infrastructure spanning cloud, on-prem, and hybrid environments. You will partner with engineering, security, and operations to enable secure software delivery and provide paved paths for developers.

The role emphasizes scalable architecture, automation, and observability, with close collaboration across teams to improve reliability and development productivity in a dynamic defense-tech setting.