- Company Name
- SmartCo Consulting
- Job Title
- GCP Cloud Engineer
- Job Description
-
**Job title:**
GCP Cloud Engineer / DevOps Engineer – GenAI
**Role Summary:**
Contract role commencing January 2026. Design, build, and maintain GCP infrastructure for large‑scale AI workloads in a regulated financial services program. Lead the migration of AI components from AWS/Azure to GCP, develop CI/CD pipelines, deploy containerized GenAI services, and ensure secure, scalable, and cost‑optimized operations.
**Expactations:**
- Deliver end‑to‑end GCP infrastructure for GenAI solutions on a qualified contract schedule.
- Translate multi‑cloud AI components into GCP‑native services (Vertex AI, Gemini, Document AI, Vision API).
- Collaborate with AI engineering teams, enforce DevSecOps best practices, and provide observability for AI workloads.
**Key Responsibilities:**
- Architect and provision secure, compliant GCP environments (Compute Engine, GKE, Cloud Run, Cloud Functions, Vertex AI, BigQuery).
- Create and maintain IaC using Terraform; build and maintain GitHub/GitLab/CI pipelines.
- Deploy, scale, and monitor containerized workloads with Docker and GKE.
- Design and support GenAI pipelines: vector databases, embeddings, RAG workflows, and model deployment.
- Implement observability (Cloud Monitoring, Cloud Logging) and automation for AI services.
- Optimize cost and governance, enforce IAM, VPC, and security controls.
- Work within regulated financial services standards and compliance requirements.
**Required Skills:**
- Deep experience with GCP services: Compute Engine, GKE, Cloud Run, Cloud Functions, Vertex AI, Gemini, Document AI, Vision API, BigQuery, IAM, Cloud Storage, Deployment Manager/Terraform.
- Proven expertise in DevOps: CI/CD (GitHub Actions, Jenkins, GitLab CI), containerization (Docker, Kubernetes).
- Practical knowledge of GenAI tools across cloud platforms (AWS Bedrock, SageMaker, Azure AI Foundry, Databricks).
- Scripting in Python or Bash; familiarity with vector databases, embeddings, and RAG architecture.
- Strong cloud security, networking, and identity management foundation.
- Experience architecting AI‑centric GCP infrastructures; prior regulated industry exposure preferred.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Engineering, or related technical field (or equivalent hands‑on experience).
- Certifications such as Google Professional Cloud Architect, Google Professional Cloud Developer, or equivalent DevOps certifications (e.g., GCP Professional DevOps Engineer).