Senior DevOps Engineer

Description

The company's Sovereign Cloud unit is newly set up inside its Product Engineering group. It brings together the Sovereign Cloud offering for the public sector and regulated industries and works across every board area to build one scalable delivery model.

The company has operated for over 50 years and builds enterprise applications and business AI for customers and partners worldwide.

You join a senior engineering community where you work across product lines and mentor teams to deliver secure, scalable cloud services. At this level you own hard engineering problems on your own and help set the programme's technical direction.

Responsibilities

• Work closely with product owners, architects, security engineers and programme managers.
• Lead the design and build of the infrastructure tooling that Sovereign Cloud operations depend on.
• Drive proofs of concept and move the tools they validate into live environments.
• Automate cloud delivery and provisioning at scale with Infrastructure as Code.
• Investigate complex infrastructure faults and fix their root causes so the fixes hold.
• Coach junior engineers and support their technical growth.
• Work with security and architecture colleagues to define technical standards.

Requirements

• Deep experience with Infrastructure as Code tools, Terraform and Ansible in particular.
• Solid working knowledge of AWS, GCP, Azure and OpenStack.
• Expertise in Kubernetes, including converting virtual machine workloads into containers.
• Skill with scripting languages and cloud automation pipelines.
• A degree in computer science, engineering or a related field, or equivalent experience.
• Fluent written and spoken English.
• Willingness to go through a government security clearance process, since the work may be classified.
• Experience taking full ownership of complex tooling problems in enterprise settings that serve regulated industries.
• Trust-building, clear communication, a customer-first approach, emotional intelligence and real problem-solving ability.
• Comfort using AI tools every day, including agentic AI: writing effective inputs, automating routine work, checking AI output quality and helping teams adopt AI practices.
• Mastery of ML lifecycle automation, infrastructure design and performance tuning. You champion MLOps principles and coach peers in best practice.

Conditions

Travel of up to 10% of the time.

The actual salary falls within the published range and depends on education, skills, experience, location and role scope, as decided through selection.

The company practises equal opportunity and offers accessibility accommodations to applicants with physical or mental disabilities.

Candidates must follow the company's ethical AI guidelines for recruitment, and a breach may lead to removal from the hiring process.

Benefits

• Variable incentives may be offered where applicable, under the relevant plans and policies.
• Any incentive is target-based, with payouts depending on company and individual performance.
• Additional benefits apply subject to plan terms, and a summary of North America benefits and eligibility is available.
• Employees may refer candidates through the referral programme, but only for permanent roles.