Your main responsibilities will include, but are not limited to:
* Build, configure and improve GCP infrastructure foundations using Terraform and automated delivery pipelines.
* Implement reusable infrastructure-as-code modules for projects, networking, IAM, service accounts, secrets, logging, monitoring, and policy guardrails.
* Support secure GCP landing-zone patterns, including organization and project structure, Shared VPC, network segmentation, private connectivity, firewall policies, and environment isolation.
* Create and maintain CI/CD pipelines for provisioning, validation, testing, deployment, and lifecycle management of platform components.
* Implement identity and access patterns such as federation, workload identity, least-privilege IAM, service account governance, and secure access workflows.
* Support GCP data and AI platform enablement, including platform patterns for Vertex AI, BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Composer, and related integration services.
* Build observability and operational controls using Cloud Logging, Cloud Monitoring, alerting, dashboards, runbooks, and production-readiness checks.
* Translate platform priorities and agreed engineering standards into well-structured backlog items, engineering tasks, implementation plans, and technical documentation.
* Collaborate with cybersecurity, governance and architecture teams to ensure platform capabilities meet security, compliance, and operational expectations.
* Contribute to code reviews, pattern reviews, testing practices and continuous improvement of the GCP platform engineering experience.
Key skills required for this role:
* GCP infrastructure: Hands-on experience with GCP projects, networking, Shared VPC, Cloud NAT, firewall policies, private connectivity, and environment separation.
* Terraform and IaC: Strong Terraform skills, including module usage, reusable patterns, state handling, variables, outputs, validation, and promotion across environments.
* IAM and security: Practical knowledge of IAM, least privilege, service accounts, workload identity, federation, secrets management, key management, and secure access patterns.
* CI/CD and automation: Experience building or operating pipelines for infrastructure provisioning, validation, deployment, policy checks, and release management.
* Data and AI platform services: Working knowledge of GCP services such as Vertex AI, BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Composer, Cloud Run, or GKE.
* Observability and operations: Experience with Cloud Logging, Cloud Monitoring, alerting, dashboards, runbooks, incident response, and production-readiness practices.
* Engineering collaboration: Ability to work in a team, write clear documentation, participate in reviews, and communicate technical decisions clearly.
Our requirements
Who you are
This is the right role for you if you:
* You are hands-on: You enjoy building infrastructure, automation, and platform capabilities that are robust, reusable, and easy for others to consume.
* You care about secure engineering: You understand that identity, access, network boundaries, auditability, and operational controls are core parts of platform delivery.
* You are delivery focused: You can take agreed priorities and engineering standards, break them into concrete tasks, and deliver working outcomes with quality and discipline.
* You are curious about AI platforms: You want to help make data and AI capabilities available in a controlled, scalable, and developer-friendly way.
* You collaborate well: You communicate clearly, ask good questions, and work constructively with engineers, architects, and governance stakeholders.
What we're looking for:
Education and Experience:
* A BSc or MSc in Computer Science, Engineering, Information Security, Data Engineering, or a related discipline, or equivalent practical experience.
* Several years of experience in cloud engineering, infrastructure engineering, platform engineering, DevOps, or similar roles.
Required qualifications:
* Practical experience building or operating production-grade infrastructure on GCP.
* Strong Terraform and automation experience, with an understanding of reusable module design and infrastructure lifecycle management.
* Solid understanding of cloud networking, IAM, security controls, secrets management, and operational monitoring.
* Experience with CI/CD tools and modern software engineering practices such as code review, version control, testing, and documentation.
* Interest in GCP data and AI services, especially Vertex AI, BigQuery, Dataflow, and related platform capabilities.
* Ability to work in a regulated enterprise environment where compliance, resilience, and auditability matter.
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