Principal Cloud Foundations Engineer – GCP

GSK remains committed to achieving bold commercial ambitions for the future. By 2031, we aim to deliver £40 billion in annual sales, leveraging our existing strong performance momentum to significantly increase our positive impact on the health of billions of patients globally.

The Principal Cloud Foundations Engineer – GCP builds and runs the foundation of Google Cloud platform as automated, secure, self-service infrastructure, sets the engineering standard within that platform, mentors the engineers around them, and treats the teams who consume the platform as customers.

Key Responsibilities

• Design, build and automate platform infrastructure using infrastructure-as-code and golden paths, so that provisioning is repeatable rather than reconstructed each time.
• Use AI-assisted engineering across code generation, review and testing to accelerate delivery and raise quality, reviewing AI-generated output before it is merged.
• Build self-service capabilities and paved roads that reduce friction for consuming teams, so adoption does not depend on the platform team's availability.
• Engineer for reliability by defining SLOs, instrumenting platforms for observability and automating to reduce toil, working with the Site Reliability Engineer on standards.
• Set and uphold engineering standards, secure-by-default practices and code quality within the platform, and hold them in code review.
• Contribute to incident response and drive permanent automated fixes with Reliability Engineering rather than repeating manual recovery.
• Mentor and technically lead other engineers, including partner engineers, linking engineering work to platform OKRs and outcomes.
• Integrate and assure supplier or managed-service components, holding partner-delivered engineering to the same standards and code quality as internal work.
• Work the platform's manual task and toil backlog, converting identified candidates into automation and evidencing the effort removed.
• Close observability coverage gaps for the platform, so that reliability can be measured rather than inferred.
• Contribute engineering-led items to the platform backlog held by the Product Owner, including technical debt, upgrade and automation work, with the cost of not doing them stated.
• Apply the reference architectures and patterns set by the Platform Architect, and raise a case for change rather than diverging locally.

Education & Professional Qualifications

• Degree in a technology or engineering discipline, or equivalent practical experience (e.g., Computer Science, Software Engineering, Electronics).
• Relevant technical certifications desirable (e.g., a recognised cloud certification for AWS, GCP or Azure, Certified Kubernetes Administrator, or a network vendor certification relevant to the platform).

Area of Specialisation

• Hands-on platform engineering in cloud, network or digital workplace, covering infrastructure-as-code, CI/CD and containers where relevant.
• Automation-first and secure-by-default engineering, with an SRE mindset covering SLOs, observability and toil reduction.

Experience Required

• Overall 15 years and typically 6-8 years in cloud, infrastructure or software engineering, including at least two years as the senior technical voice in a team.
• Experience deploying landing zones and services in Google Cloud Platform (GCP).
• Practical experience of infrastructure-as-code, for example Terraform, applied to production estates rather than proofs of concept.
• Experience with CI/CD pipelines, and with containers and Kubernetes where relevant to the platform.
• Track record building self-service capability that other teams adopted without hand-holding.
• Experience instrumenting for observability, defining SLOs and reducing toil through automation.
• Experience with AI-assisted engineering tooling, including judgement about when generated output is not fit to merge.

Desirable:

• Certifications in cloud platforms (e.g. Google Professional Cloud Architect, Azure Solutions Architect Expert).
• Knowledge of Cloud Cost methodology
• Familiarity with multi-cloud deployments using cloud tools like Camunda, GitHub Action, Azure Arc, Google Anthos etc.
• Knowledge of Pharma practices, GxP, Validation, Audit readiness and how to optimize delivery to accommodate these critical practices

Related Skills/Background

• Automation-first instinct, treating a repeated manual task as a defect rather than as work.
• Code review discipline, holding quality without becoming a bottleneck.
• Mentoring ability with engineers of varying experience, including partner engineers outside the line.
• Judgement about when AI-generated code is fit to merge and when it is not.
• Customer mindset toward consuming teams, who can route around a platform that is hard to use.
• Willingness to make technical debt and its cost visible rather than absorbing it silently.