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GCP Cloud Engineer

Neurons Lab

Roma

Ibrido

EUR 70.000 - 90.000

Tempo pieno

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Descrizione del lavoro

A technology consultancy is seeking a Senior GCP Cloud Engineer in Rome. The role involves building and maintaining cloud infrastructure on the Google Cloud Platform with a focus on security, compliance, and operational excellence, particularly for Generative AI solutions in the banking sector. Candidates should have strong experience in Terraform, Kubernetes, Docker, and Python. The position is part-time with a long-term engagement and project-based allocations.

Competenze

5+ years in cloud engineering, DevOps, or solution architecture roles.
GCP experience required, AWS is a strong plus.
2+ years hands-on with Terraform and Kubernetes.

Mansioni

Build and maintain GCP infrastructure using Terraform.
Deploy applications on GKE and manage Kubernetes.
Develop and deploy GenAI model serving on GCP.

Conoscenze

Terraform

Kubernetes

Docker

Python

Google Cloud Platform

CI/CD pipelines

Linux/UNIX

GenAI

Formazione

Google Cloud Certified Professional Cloud Architect

Strumenti

Google Cloud services

Docker

Terraform

Kubernetes

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