**About the project** --------------------- Join Neurons Lab as a **Senior GCP Cloud Engineer** working on **Generative AI solutions for banking clients**. You'll be hands\-on building production infrastructure on Google Cloud Platform while contributing to architecture design, with a strong focus on security, compliance, and operational excellence. **Our Focus**: Banking and Financial Services clients with stringent regulatory requirements (PCI\-DSS, GDPR, MAS TRM). You'll architect and implement GenAI solutions \- from RAG systems to ML platforms \- while ensuring enterprise\-grade security and compliance. **Your Impact**: Build cloud infrastructure using **Terraform, Kubernetes, and Docker**. Work across multiple banking GenAI projects, implementing architectures, creating reusable IaC patterns, and maintaining the highest security 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 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 **KPI** ------- * 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 \- must be active/current) * 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, security, networking, Helm * **Docker** (expert level) \- 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 requirements (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, etc.) \+ **AWS experience is a strong plus** * **2\+ years** with **Terraform** for GCP \- reusable modules, automation, standardization * **2\+ years** with **Kubernetes** (GKE preferred) and **Docker** \- production clusters, security * **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 (please mention up to 5 questions** -------------------------------------------------------------- * **GCP Certification**: Please confirm your **Google 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, Gemini, 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\-DSS, GDPR, etc.), and security 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.