Senior Principal - Cloud Platform Engineer – Cloud Native
GSK is hiring a Senior Principal - Cloud Platform Engineer – Cloud Native for a remote role open to applicants in India. Level rates it ; you can apply on GSK.
Level's read on this job
- Level rates this role Little AI ●○○○: aI is not part of the work.
- This is listed as a remote role.
- The posting mentions OpenAI and Azure OpenAI among its tools and skills.
- GSK has 822 other open roles on Level.
- Posted in the last few days.
AI in this role
Business Introduction
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. Our Ahead Together strategy is centred on early intervention to prevent and alter the course of disease, thereby protecting people and supporting healthcare systems.
Our diverse portfolio consists of vaccines, specialty medicines, and general medicines.
Through continuous innovation and a dedicated focus on scientific and technical excellence, we strive to develop and launch new, groundbreaking treatments that address critical health challenges.
Job Purpose
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. The role works through infrastructure-as-code and golden paths rather than manual configuration, uses AI-assisted engineering across code generation, review and testing, and engineers reliability in by defining SLOs, instrumenting for observability and automating away toil.
This is the senior hands-on engineering role in the platform team, insourced at the grades covered by this description while engineering at G7b and below is delivered through managed service partners, so the role integrates and assures partner components as well as building. Engineering roadmap and direction sit with the Engineering Director, reference architecture and standards sit with the Platform Architect, backlog order sits with the Product Owner, and deep reliability engineering sits with the Site Reliability Engineer deployed from Reliability Engineering & Operations.
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.
Desirable:
- Proficient in building solutions using container services - AKS & GKE
- Hands-on experience deploying container solutions, including Docker containers, and managing K8s deployments using YAML and Helm charts
- 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
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.
#AGTech
Skills
Why GSK?
Uniting science, technology and talent to get ahead of disease together.
GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.
People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.
Inclusion at GSK:
As an employer committed to Inclusion, we encourage you to reach out if you need any adjustments during the recruitment process.
Please contact our Recruitment Team at IN.recruitment-adjustments@gsk.com to discuss your needs.
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How we rate this
Senior Principal - Cloud Platform Engineer – Cloud Native at GSK rates 20 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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