Google Cloud Platform Architect

Sanderson Recruitment Plc
Glasgow, UK
5 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
£117,000.0
Working hours
Regular working hours

Tech stack

Clean Code Principles Application Programming Interfaces (APIs) Artificial Intelligence Cloud Computing Cloud Engineering Computer Programming Continuous Integration Distributed Systems Python (Programming Language) Systems Development Life Cycle Google Cloud Cloud Platform System
+5 more
GitHub Copilot Delivery Pipeline Reliability of Systems Kubernetes Infrastructure Automation Frameworks

Requirements

This role requires a highly experienced GCP Architect, who can design and deliver complex cloud-native solutions, make strategic architectural decisions, and solve ambiguous technical challenges. The successful candidate will develop secure, high-quality code, lead architecture reviews and create design artefacts such as RFCs, ADRs and architecture diagrams that influence multiple teams.

A key responsibility is driving operational excellence by improving system reliability, scalability, performance, and observability. The role also involves evaluating new technologies and vendors, shaping cloud platform strategy, and contributing to the adoption of best practices in areas such as CI/CD, infrastructure as code, and cloud-native engineering.

The position carries a strong leadership component, including mentoring engineers, leading communities of practice and raising engineering standards across the organisation.

Key experience (A blend of):

  • 5+ years of production software engineering experience with strong system design and development skills
  • Hands-on Google Cloud Platform (GCP) experience, building and operating cloud-native workloads
  • Expertise in cloud architecture, distributed systems, security, AI/ML or platform engineering
  • Advanced programming expertise in Go and/or Python
  • Kubernetes platform engineering experience, including CRDs and API extensions.
  • Strong knowledge of Kubernetes internals, multi-tenancy and observability
  • Proven experience with CI/CD, automation, infrastructure as code and deployment pipelines.
  • Strong understanding of SDLC, Agile delivery, resiliency and security
  • Practical use of AI-assisted development tools such as GitHub Copilot or Claude Code.
  • Excellent stakeholder management, communication, and technical leadership skills.

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