> Markdown version of [/jobs/ext/4584587-gcp-architect-technical-lead](https://www.wearedevelopers.com/jobs/ext/4584587-gcp-architect-technical-lead). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # GCP Architect / Technical Lead - **Company:** Flexon Technologies Inc - **Location:** Tampa, FL, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, BigQuery, Cloud Computing, Cloud Engineering, Cloud Storage, Identity and Access Management, Platform as a Service (PAAS), Cloud Services, Data Logging, Google Cloud, Cloud Monitoring, Generative AI, Apigee, Backend, AI Platforms, Front End Software Development, Api Gateway, Terraform - **Published:** November 5, 2026 - **Apply:** https://www.juju.com/job/2_172415101 ## About the Role Strong hands-on experience with Google Cloud Platform (GCP). - Experience designing solutions using GCP-native PaaS / managed services. - Strong cloud solution architecture experience. - Experience working with Google Cloud AI capabilities/services. - Experience designing integrations between cloud services and applications. - Ability to provide hands-on technical leadership in a fast-moving project. xrbllit - Strong communication and stakeholder collaboration skills. Preferred / Relevant GCP Experience: Candidates with practical experience across several of the following would be particularly relevant: - Vertex AI / Generative AI on Google Cloud - Cloud Run - Cloud Functions - API Gateway / Apigee - Pub/Sub - Cloud Storage - BigQuery - Cloud SQL / Firestore - IAM and service accounts - Secret Manager - Cloud Logging / Cloud Monitoring - Terraform or equivalent Infrastructure as Code ## Description Own the overall GCP solution architecture and technical direction. - Design a cloud-native architecture using appropriate GCP PaaS and managed services. - Identify opportunities to use Google Cloud AI services within the solution. - Guide the engineering team on GCP architecture, integration, security, scalability, and deployment considerations. - Recommend GCP-native approaches rather than relying primarily on generic container-based solutions. - Collaborate with consulting and application teams as the frontend/backend requirements become clearer.