Cloud Solutions Architect Aguadilla - Puerto Rico

Role Descriptions:

Key Responsibilities

Design, build, deploy, and support scalable, secure, and high-availability solutions on Google Cloud Platform (Google Cloud Platform).

Implement and manage cloud services including GKE, Compute Engine, Cloud Run, Cloud Functions, Cloud Storage, BigQuery, and Cloud SQL.

Develop Infrastructure-as-Code (IaC) using Terraform and automate deployments through CICD pipelines.

Build and manage containerized applications using Docker and Kubernetes.

Develop and deploy Generative AI solutions using Google Gemini and Vertex AI, including AI agents, chatbots, document intelligence, and workflow automation.

Implement RAG (Retrieval Augmented Generation) architectures, prompt engineering, vector databases, and enterprise AI integrations.

Ensure cloud security, IAM governance, monitoring, logging, performance optimization, and cost management.

Collaborate with business, architecture, and development teams to deliver cloud and AI transformation initiatives.

Required Qualifications

Bachelors degree in Computer Science, Engineering, Information Technology, or related field.

5-10 years of IT experience, including 3+ years of hands-on Google Cloud Platform experience.

Strong expertise in Google Cloud Platform services, cloud architecture, networking, security, and DevOps practices.

Experience with Terraform, Kubernetes, Docker, GitHubGitLab, CICD, and automation frameworks.

Hands-on experience building AIGenAI applications using Google Gemini, Vertex AI, LangChainLangGraph, and API integrations.

Strong programming skills in Python and scripting languages.

Experience with monitoring, troubleshooting, and supporting production cloud environments.

Excellent communication, stakeholder management, and problem-solving skills.

Preferred Certifications

Google Cloud Professional Cloud Architect

Google Cloud Professional DevOps Engineer

Google Cloud Generative AI Engineer (preferred)

Nice-to-Have (PharmaLife Sciences Environment)

Experience supporting Life Sciences, Clinical, R&D platforms.

Understanding of GxP, CSACSV validation, and regulated cloud environments.

Knowledge of data governance, privacy, and compliance requirements within pharmaceutical organizations.

Experience working with enterprise AI governance and responsible AI frameworks in regulated industries.