Description
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 Platform Engineer - Cloud Native builds and runs automation scripts and tools (IaC / Terraform) to streamline provisioning, configuration, and management of Cloud PaaS and Serverless Services, and sets the engineering standard within those services, 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.
Educational Background
- 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
- Typically 6-8 years in cloud, infrastructure or software engineering, including at least two years as the senior technical voice in a team.
- Deep hands-on depth in Cloud PaaS and Serverless Technologies across Azure, Azure Local and GCP.
- Proficient in writing scripts using Terraform, Python, Ansible, Json and PowerShell.
- Experience with building, configuring and managing Cloud AI Services (e.g. Azure OpenAI, AI Search, Azure Machine Learning, Google Document AI, BigQuery AI).
- Practical experience of infrastructure-as-code, for example Terraform, applied to production estates rather than proofs of concept.
- Strong expertise in Azure/GCP application services (e.g. Logic Apps, Function Apps, App Services, cloud run, pub/sub) for designing and implementing scalable, secure, and cloud-native solutions.
- 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.
Benefits
- GSK offers a range of benefits to support employees' well-being and career growth.