GCP Architect
Elevate your career as a GCP Architect by spearheading innovative cloud solutions within a highly regulated pharmaceutical environment. This pivotal role combines deep expertise in Google Cloud Platform with a focus on AI, compliance, and secure enterprise delivery. Join a team dedicated to pushing the boundaries of cloud infrastructure, AI deployment, and validation—making a direct impact on life sciences and healthcare innovations.
Key Responsibilities
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Design & Support GCP Infrastructure: Build and optimize Google Cloud environments supporting AI applications, ensuring scalability, security, and compliance across development, testing, staging, and production. Manage services like Vertex AI, BigQuery, Cloud Run, GKE, Cloud Storage, and more.
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DevOps & Automation: Develop and maintain robust CI/CD pipelines for applications and infrastructure, emphasizing reproducibility, validation readiness, and automated evidence collection. Utilize infrastructure-as-code tools such as Terraform to promote consistency.
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Security & Compliance: Implement stringent cloud security controls, including IAM policies, secrets management, network segmentation, encryption, and audit trails. Collaborate with security teams to uphold industry standards and regulatory requirements.
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Observability & Incident Management: Deploy comprehensive monitoring, logging, alerting, and dashboarding to ensure high availability and quick incident response. Support operational stability and performance tuning.
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AI and Model Operations: Support deployment, evaluation, and lifecycle management of AI models using Vertex AI, Gemini, and Claude. Enable traceability, version control, and observability for AI-driven solutions aligning with validation needs.
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Validation & Audit Readiness: Document deployment processes, configuration changes, and operational evidence necessary for life sciences regulatory audits. Ensure environments meet GxP, CSV, and other compliance standards.
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Cross-Functional Collaboration: Partner with AI architects, data engineers, security specialists, QA, and project teams. Participate in agile ceremonies and ensure smooth delivery and deployment workflows.
Required Skills
- Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
- 5+ years in DevOps, Cloud, Platform, or Infrastructure Engineering.
- Hands-on experience supporting production systems on Google Cloud Platform.
- Expertise with GCP services like Vertex AI, BigQuery, Cloud Run/GKE, Cloud Storage, Dataflow, Composer, Document AI, Cloud Logging, and Cloud Monitoring.
- Proven ability to develop and manage CI/CD pipelines and infrastructure as code (preferably Terraform).
- Strong understanding of cloud security principles, IAM, secrets management, network security, encryption, and environment segregation.
- Experience with container orchestration tools such as Kubernetes, Docker, and Cloud Run.
- Excellent documentation skills covering deployment steps, configuration evidence, operational procedures, and change management.
- Effective communicator capable of collaborating across technical and business teams.
- Must be authorized to work in the United States without current or future sponsorship.
Nice to Have Skills
- Experience supporting AI, machine learning, LLM, or data-intensive applications in production.
- Knowledge of Vertex AI, Gemini, Claude, model deployment workflows, prompts, and observability tailored to AI systems.
- Experience working in highly regulated environments such as pharmaceutical, biotech, medical devices, or healthcare.
- Familiarity with GxP, 21 CFR Part 11, GAMP 5, CSV, CSA, or comparable validation standards.
- Knowledge of advanced secure cloud architectures, including VPC Service Controls, CMEK, and identity federation.
- Cost and FinOps practices: cloud cost monitoring, inference cost management, and capacity planning.
Preferred Education & Experience
- Bachelor’s degree in relevant field; advanced degree a plus.
- Extensive hands-on experience (5+ years) supporting cloud infrastructure, especially in regulated industries.
- Certifications such as Google Cloud Professional Cloud Architect, Cloud DevOps Engineer, Cloud Security Engineer, or Machine Learning Engineer highly desirable.
Other Requirements
- Remote work opportunity with the ability to collaborate globally.
- Availability for occasional stakeholder engagement and operational support outside standard hours as needed.
- Commitment to compliance, validation, and audit readiness in highly regulated environments.
This role offers a unique opportunity to influence cutting-edge cloud AI solutions within a regulated and impactful domain. Be part of a team that values innovative problem-solving, operational excellence, and a security-first mindset.
