Staff Engineer, Digital Infrastructure & Cloud Automation

Shield AI; London; On-site; NOK 1,141,000 - 1,775,000; Full time

Job summary

Shield AI in London seeks an experienced engineer to deploy, integrate and maintain components of our autonomy software factory. You will work with cloud-native tooling, Kubernetes, and C++/Python applications to ship AI training and deployment pipelines on site.

Strong Linux networking, distributed systems debugging, and collaboration with cross-functional teams are essential. Onsite presence at the London office is required.

Qualifications

• 7+ years of related experience with a degree or 6 years with a master’s degree or 4 years with a PhD; or equivalent work experience.
• 3+ years cloud computing experience with Kubernetes and container orchestration.
• Experience supporting C++ or Python-based applications.
• Solid Linux/Unix networking knowledge; design and implement networked applications.
• BS/MS in Computer Science or equivalent practical experience.
• Proven teamwork, high standards, and collaborative mindset.
• Experience debugging deployed distributed systems.
• Experience developing automation tooling (Ansible, Chef, Puppet).
• Must be available to support onsite in our London office.

Responsibilities

• Work with a small team of engineers and administrators.
• Integrate our AI training factory and tooling onto new hardware.
• Provide software updates and configuration management between various isolated environments.
• Ensure proper operation of our AI training factory and tooling.
• Coordinate with autonomy teams to build and meet requirements.
• Solve challenging and important problems.

Skills

Kubernetes

C++

Python

Linux networking

Distributed systems debugging

Automation tooling

Education

Bachelor's degree in Computer Science or equivalent

Job description

Shield AI in London seeks an experienced engineer to deploy, integrate and maintain components of our autonomy software factory. You will work with cloud-native tooling, Kubernetes, and C++/Python applications to ship AI training and deployment pipelines on site.

Strong Linux networking, distributed systems debugging, and collaboration with cross-functional teams are essential. Onsite presence at the London office is required.