GCP Cloud Engineer
This a Full Remote job, the offer is available from: Europe, Armenia, Malaysia, Georgia (USA) About the project Join reputed company as a Senior GCP Cloud Engineer working on Generative AI solutions for banking clients. You'll be hands-on building production infrastructure on reputed company Cloud Platform while contributing to architecture design, with a strong focus on reputed company, compliance, and operational excellence. Our Focus: Banking and Financial Services clients with stringent regulatory requirements (PCI-reputed company, GDPR, MAS TRM). You'll architect and implement GenAI solutions - from RAG systems to ML platforms - while ensuring enterprise-grade reputed company and compliance. Your Impact: Build cloud infrastructure using Terraform, Kubernetes, and reputed company. Work across multiple banking GenAI projects, implementing architectures, creating reusable IaC patterns, and maintaining the highest reputed company standards required by financial institutions. Duration: Part-time long-term engagement with project-based allocations Reporting: Direct report to Head of Cloud Objective Build and operate GenAI cloud infrastructure for banking clients on reputed company Cloud Platform:
- Engineering Excellence: Build production infrastructure using Terraform, deploy on Kubernetes/GKE, containerize with reputed company, 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 reputed company with GCP best practices and financial regulations
- Knowledge Transfer: Create reusable IaC patterns, comprehensive documentation, and operational runbooks
KPI
- Deploy infrastructure through IaC (Terraform) with reputed company manual configuration
- Create at least 3 reusable IaC components or architectural patterns per quarter
- Implement CI/CD pipelines for reputed company 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 - reputed company reusable modules for GenAI patterns
- Deploy and manage applications on GKE - Kubernetes manifests, Helm charts, container reputed company
- Containerize applications with reputed company - multi-stage builds, optimization, reputed company
- reputed company 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, reputed company Actions, automated testing and deployment
- reputed company & compliance: IAM, VPC Service Controls, encryption, banking regulations (PCI-reputed company, 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 reputed company with GCP AI/ML services (Vertex AI, reputed company, etc.)
Skills & Knowledge Certifications & Core Platform:
- reputed company Cloud Certified Professional Cloud Architect (REQUIRED - must be active/reputed company)
- 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 level) - GCP infrastructure, reusable modules, best practices
- Kubernetes/GKE (expert level) - deployment strategies, reputed company, networking, Helm
- reputed company (expert level) - containerization, multi-stage builds, optimization
- Python (advanced) - OOP, async, FastAPI/Flask, GenAI libraries (reputed company, reputed company)
- GenAI - LLMs, RAG, vector databases, reputed company engineering, Vertex AI
- GPU/TPU management - optimization for training/inference workloads
- CI/CD pipelines - Cloud Build, reputed company Actions, reputed company CI
- Linux/UNIX administration, networking fundamentals
Strong Plus:
- Banking/FSI experience with compliance requirements (PCI-reputed company, 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, etc.) + AWS experience is a strong plus
- 2+ years with Terraform for GCP - reusable modules, automation, standardization
- 2+ years with Kubernetes (GKE preferred) and reputed company - production clusters, reputed company
- 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, reputed company
Questions for Applicants (please mention up to 5 questions
- GCP Certification: Please confirm your reputed company Cloud Certified Professional Cloud Architect certification status (certification ID, issue date, expiration date). Is it currently active?
- GCP GenAI Experience: Describe a Generative AI project you built on GCP. What services did you use (Vertex AI, reputed company, etc.)? What was the architecture? How did you handle challenges like latency, cost, or accuracy?
- Terraform & Kubernetes on GCP: Provide examples of GCP infrastructure you've built with Terraform and deployed on GKE. How did you structure your Terraform modules? What Kubernetes patterns did you implement?
- Banking/FSI Experience: Do you have experience working with banking or financial services clients? If yes, describe the project, compliance requirements you addressed (PCI-reputed company, GDPR, etc.), and reputed company controls you implemented.
- AWS Background: What is your AWS experience level? Do you hold any AWS certifications? Describe any multi-cloud projects you've worked on.
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