Cloud & Hosting - Principal Platform Engineer – DevSecOps / DevEx
GSK (company site, opens in a new tab)6–8 yrsBengaluruOn-siteDirect career pageEst. 28–42 LPA
Posted 9h ago
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Reach people at GSK
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at GSK you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, automate, and maintain secure, self-service modern engineering platforms using infrastructure-as-code and AI-assisted engineering to improve reliability and reduce manual work.
- Set and enforce engineering standards, mentor engineers including partners, and integrate/managing supplier or managed-service platform components.
- Collaborate on incident response and reliability engineering through observability, defining SLOs, and automating remediation in partnership with SRE teams.
Minimum Requirements
- 6-8 years in platform, infrastructure, or software engineering, including at least 2 years as senior technical lead.
- Hands-on experience with container services (AKS & GKE), Kubernetes deployment and management using YAML/Helm charts.
- Proficiency in Linux/Red Hat platforms, Ansible Automation, infrastructure-as-code tools (e.g., Terraform) applied in production.
- DevSecOps and CI/CD experience with GitHub/GitHub Actions or Azure DevOps, including security scanning, secrets management, and artifact management.
Ideal Candidate Profile
- Experienced senior engineer comfortable leading platform architecture and mentoring diverse engineering teams, including external partners.
- Skilled at building scalable self-service platforms adopted widely without dependence on platform team availability.
- Practiced in automation-first mindset, observability instrumentation, defining and enforcing SLOs, and experienced in adjudicating AI-assisted engineering outputs.