Senior Principal Platform Engineer – DevSecOps / DevEx

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  Keep GSK’s standard company introduction (Ahead Together, portfolio, innovation) unchanged above this section.  The Senior Principal Platform Engineer – DevSecOps / DevEx is the senior technical owner of GSK’s Modern Engineering platforms: Red Hat Ansible Automation Platform, GitHub Enterprise, Azure DevOps, observability and the Nuro AIOps control plane. Every D&T delivery team builds, ships and runs on these platforms, across Azure and GCP, in a GxP-regulated environment.  You run them as secure, self-service products. You set the engineering standard, build golden paths and infrastructure as code instead of manual configuration, and engineer reliability through SLOs, observability and automation. You build agentic AI and AIOps automation that moves the platforms towards self-healing, autonomous operations, with guardrails and human approval where it matters. You treat consuming teams as customers and measure success by adoption, speed and security, not uptime alone.  Key Responsibilities Platform ownership: run each platform as a product with SLOs, a capacity plan and a lifecycle (patching, upgrades, end-of-life). Feed engineering-led items into the Product Owner’s backlog, including technical debt and upgrades, with the cost of not doing them stated.  Reliability: achieve 99.9% availability for tier-1 platforms. Lead technical incident response with Reliability Engineering, run blameless post-incident reviews and drive permanent automated fixes instead of repeated manual recovery. Close observability gaps so reliability is measured, not inferred.  Everything as code: manage platform config, policies, pipelines and dashboards in Git through Terraform, Ansible, Helm and GitOps, so provisioning is repeatable. Use AI-assisted engineering across code generation, review and testing, and review AI-generated output before it is merged.  Secure by default: enforce SSO, least-privilege RBAC, secrets management, signed artefacts, branch protection and supply-chain controls (SLSA, SBOM, GitHub Advanced Security) inside the golden path, not bolted on afterwards.  Golden paths: build reusable templates, pipelines and automation content for developer platforms / automation platforms like GitHub, ADO, AAP, Azure/GCP, so delivery teams self-serve without tickets or the platform team’s time.  AI Agentic automation: Design and code agentic AI agents for self-healing and autonomous operations, with human approval gates, guardrails and audit trails.  Compliance: keep platforms in a validated state for GxP, SOX and data-privacy controls, and produce audit evidence automatically from the pipeline.  Toolchain rationalisation: be the technical lead for the platforms strategy, including migration plans, licence optimisation and FinOps for runners and hosting.  Developer experience: measure and improve DORA metrics and platform NPS; work the toil backlog and evidence the effort removed; run onboarding, documentation and office hours.  Leadership: set and uphold engineering standards in design and code review, applying the Platform Architect’s reference architectures and raising a case for change rather than diverging. Mentor internal and partner engineers, hold supplier-delivered work to the same standard, and manage technical relationships with Red Hat, GitHub, Microsoft and Google.  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 platform, infrastructure or software engineering, including at least two years as the senior technical voice in a team. Proven experience as a DevOps, Cloud Engineer with design experience 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.undefined Experience of creating Agentic AI agents for Self-Healing & Autonomous Operations undefined Familiarity with service discovery tools like Istio & Mesh undefined Expert in using GitHub, GitHub Actions, Azure DevOps and other configuration Tools. Practical experience of infrastructure-as-code, for example Terraform, applied to production estates rather than proofs of concept. 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).   Familiarity with multi-cloud deployments using cloud tools like Camunda, GitHub Action, Azure Arc, Google Anthos etc.   Understanding of AKS & GKE security practices   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. Skills Agentic AI, API Management, Automation Technology, Cloud Architectures, Cloud Engineering, Cloud Financial Operations, Containerization, Database Management, DevOps, DevOps Engineering, Disaster Recovery (DR), Docker Kubernetes Architecture, Edge Computing, Infrastructure As Code (IaC), Networking Concepts, Performance Optimizations, Serverless Computing, Software Engineering, System Monitors, Virtualization     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