GCP Cloud Engineer

Overview

Senior 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 Project

Join 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 Impact

• Build 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 & Reporting

Part-time long-term engagement with project-based allocations. Direct report to Head of Cloud.

Objective

Build 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.

KPIs

• Deploy 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 Responsibility

Cloud 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 & Knowledge

Certifications & Core Platform

• Google 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 Skills

• Terraform (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 Plus

• Banking/FSI experience with compliance (PCI-DSS, GDPR, MAS TRM).
• Multi-cloud architecture experience.
• Modern DevOps practices and monitoring tools.

Communication

• Advanced English (written and verbal).
• Client-facing presentations and demos.
• Technical documentation.

Experience

• 5+ 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 Applicants

• GCP 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 level

• Mid-Senior level

Employment type

• Full-time

Job function

• Engineering and Information Technology
• Industries: IT Services and IT Consulting

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