| Job Title: Google Cloud Platform Incubator Engineer |
| Function: Google Cloud Platform Incubator |
| Primary Skillset: Google Cloud Platform, Python, Terraform |
| Secondary Skillset: SDLC, Google Cloud Platform Services, Vertex AI, DevOps |
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| Job Summary |
| We are looking for a Google Cloud Platform Incubator professional with strong experience in Google Cloud Platform, Python, and Terraform to support cloud-native solution development, platform engineering, and innovation initiatives. This role will focus on building reusable cloud capabilities, accelerating prototype-to-production delivery, and enabling scalable Google Cloud Platform services adoption. The individual should have strong understanding of SDLC, DevOps practices, and modern Google Cloud Platform services, with working knowledge of Vertex AI to support emerging AI/ML use cases. |
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| Key Responsibilities |
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| Design, build, and enhance cloud-native solutions and reusable accelerators on Google Cloud Platform. |
| Develop automation scripts, utilities, and service integrations using Python to support engineering and platform needs. |
| Provision and manage Google Cloud Platform infrastructure using Terraform with a strong focus on standardization and reusability. |
| Support incubator initiatives by rapidly prototyping solutions and transitioning successful use cases into scalable implementations. |
| Collaborate with architects, developers, and business teams to translate requirements into deployable Google Cloud Platform solutions. |
| Apply SDLC best practices across design, development, testing, deployment, and handover activities. |
| Leverage core Google Cloud Platform services such as compute, storage, networking, monitoring, and security services to build robust solutions. |
| Support Vertex AI-based use cases by enabling environment setup, model workflow integration, and deployment support. |
| Implement DevOps practices including CI/CD pipeline integration, automated deployments, and environment configuration management. |
| Ensure solutions are secure, maintainable, and aligned with cloud engineering standards and governance requirements. |
| Troubleshoot platform, deployment, and integration issues and provide timely resolution during development and release phases. |
| Prepare technical documentation, deployment guides, reusable templates, and knowledge transfer materials for broader team adoption. |
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| Must-Have Skills |
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| Strong hands-on experience in Google Cloud Platform (Google Cloud Platform), including design, build, and deployment of cloud-native solutions |
| Proficiency in Python for automation, scripting, API integration, and platform engineering use cases |
| Strong experience with Terraform for infrastructure as code, reusable module creation, and environment provisioning |
| Good understanding of software development life cycle (SDLC), including design, development, testing, deployment, and support |
| Experience working with core Google Cloud Platform services such as Compute Engine, Cloud Storage, VPC, IAM, Cloud Run, GKE, BigQuery, and monitoring tools |
| Working knowledge of Vertex AI to support AI/ML environment setup, model integration, and deployment workflows |
| Experience with DevOps practices, including CI/CD pipelines, automated deployments, and configuration management |
| Ability to build reusable cloud templates, accelerators, and automation assets for scalable adoption |
| Strong troubleshooting skills for cloud infrastructure, application deployment, and service integration issues |
| Understanding of security, access control, and governance principles within Google Cloud Platform environments |
| Experience collaborating with cross-functional teams including architecture, engineering, QA, and business stakeholders |
Strong technical documentation and communication skills for solution handover and vendor coordination Regards, Radiantze Inc |
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