GCP Cloud Engineer

OverviewSenior GCP Cloud Engineer specializing in Generative AI solutions for banking clients. Hands-on building production infrastructure on Google Cloud Platform with a focus on security, compliance, and operational excellence.Location: Rome, Latium, Italy (partial remote/onsite as applicable).About The ProjectJoin Neurons Lab as a Senior GCP Cloud Engineer working on Generative AI solutions for banking clients. You will be hands-on building production infrastructure on Google Cloud Platform while contributing to architecture design with emphasis on security, compliance, and operational excellence.Your ImpactBuild cloud infrastructure using Terraform, Kubernetes, and Docker.Work across multiple banking GenAI projects, implementing architectures, creating reusable IaC patterns, and maintaining high security standards.Duration & ReportingPart-time long-term engagement with project-based allocations. Direct report to Head of Cloud.ObjectiveBuild and operate GenAI cloud infrastructure for banking clients on Google Cloud Platform.Engineering Excellence: Build production infrastructure using Terraform, deploy on Kubernetes/GKE, containerize with Docker, implement CI/CD pipelines.Architecture Support: Contribute to architecture design, create technical specifications, and provide engineering insights during solution design.Client Success: Implement secure, scalable, cost-effective solutions aligned with GCP best practices and financial regulations.Knowledge Transfer: Create reusable IaC patterns, comprehensive documentation, and operational runbooks.KPIsDeploy infrastructure through IaC (Terraform) with zero manual configuration.Create at least 3 reusable IaC components or architectural patterns per quarter.Implement CI/CD pipelines for all projects with automated testing and deployment.Document architecture and implementation details for knowledge sharing.Maintain 95%+ uptime for production GenAI endpoints.Areas of ResponsibilityCloud Engineering (70%)Build and maintain GCP infrastructure using Terraform; develop reusable modules for GenAI patterns.Deploy and manage applications on GKE; Kubernetes manifests, Helm charts, container security.Containerize applications with Docker; multi-stage builds, optimization, security.Develop Python applications: FastAPI backends, GenAI integration (RAG, LLM apps, chat interfaces).Deploy GenAI model serving: Vertex AI endpoints, containerized models on GKE, vector databases.Implement CI/CD pipelines: Cloud Build, GitHub Actions, automated testing and deployment.Security & compliance: IAM, VPC Service Controls, encryption, banking regulations (PCI-DSS, GDPR, MAS TRM).Cost optimization: GPU/TPU workload optimization, spot VMs, auto-scaling, monitoring.Manage GPU resources, ML pipelines, model performance monitoring.Architecture Support (30%)Contribute to GCP architecture design for GenAI solutions (RAG, LLM applications, ML platforms).Create technical specifications, provide cost estimates and feasibility input.Participate in technical presentations and demos.Stay current with GCP AI/ML services (Vertex AI, Gemini, etc.).Skills & KnowledgeCertifications & Core PlatformGoogle Cloud Certified Professional Cloud Architect (REQUIRED - active).Core GCP services: GCE, GKE, Cloud Run, Vertex AI, VPC, IAM, Cloud KMS, Secret Manager.AWS Certified Solutions Architect (strong plus); multi-cloud experience valued.Must-Have Technical SkillsTerraform (expert); GCP infrastructure, reusable modules, best practices.Kubernetes/GKE (expert); deployment strategies, security, networking, Helm.Docker (expert); containerization, multi-stage builds, optimization.Python (advanced); OOP, async, FastAPI/Flask, GenAI libraries (LangChain, LlamaIndex).GenAI: LLMs, RAG, vector databases, prompt engineering, Vertex AI.GPU/TPU management; optimization for training/inference workloads.CI/CD pipelines: Cloud Build, GitHub Actions, GitLab CI.Linux/UNIX administration, networking fundamentals.Strong PlusBanking/FSI experience with compliance (PCI-DSS, GDPR, MAS TRM).Multi-cloud architecture experience.Modern DevOps practices and monitoring tools.CommunicationAdvanced English (written and verbal).Client-facing presentations and demos.Technical documentation.Experience5+ years in cloud engineering, DevOps, or solution architecture roles.2+ years hands-on with GCP (GCE, GKE, Vertex AI); AWS experience is a strong plus.2+ years with Terraform for GCP – reusable modules, automation.2+ years with Kubernetes (GKE preferred) and Docker in production.2+ years Python programming – APIs (FastAPI/Flask), GenAI applications.GenAI/ML workloads (strong plus) – LLM apps, RAG systems, GPU/TPU compute.Banking/FSI experience (strong plus) – financial services clients, compliance, security.Questions for ApplicantsGCP Certification: Confirm your Google Cloud Certified Professional Cloud Architect status (cert ID, issue date, expiration).GCP GenAI Experience: Describe a GenAI project on GCP; services used; architecture; challenges.Terraform & Kubernetes on GCP: Examples of Terraform + GKE patterns; module structure.Banking/FSI Experience: Describe projects, compliance requirements, and security controls.AWS Background: Level of AWS experience and any multi-cloud projects.Seniority levelMid-Senior levelEmployment typeFull-timeJob functionEngineering and Information TechnologyIndustries: IT Services and IT ConsultingReferrals increase your chances of interviewing at Neurons Lab. 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