Google Cloud Platform Architect with AI

Job Title: Google Cloud Platform with AI/ML Expertise:

Location:  New York City, NY (Onsite)

Job Summary:

We are seeking an experienced Google Cloud Platform Architect with AI/ML expertise to design, architect, and implement scalable, secure, and high-performance cloud solutions on Google Cloud Platform (Google Cloud Platform). The ideal candidate will have deep expertise in Google Cloud Platform services and strong hands-on experience in Artificial Intelligence and Machine Learning technologies. This role involves leading cloud transformation initiatives, designing AI-driven solutions, and guiding engineering teams in best practices.

Key Responsibilities:

• Design and architect scalable, secure, and cost-effective cloud solutions on Google Cloud Platform.

• Lead AI/ML solution design using Google Cloud Platform services such as Vertex AI, AI Platform, AutoML, BigQuery ML, and TensorFlow.

• Develop cloud-native architectures leveraging GKE, Cloud Run, Compute Engine, Cloud Functions, and App Engine.

• Implement data pipelines using Dataflow, Pub/Sub, Dataproc, and BigQuery.

• Design MLOps frameworks for model training, deployment, monitoring, and lifecycle management.

• Ensure security, compliance, and governance using IAM, VPC, Cloud Armor, and encryption best practices.

• Optimize cloud performance and cost management strategies.

• Provide technical leadership and mentor engineering teams.

• Collaborate with stakeholders to translate business requirements into technical solutions.

• Stay updated with emerging AI and Google Cloud Platform technologies.

Required Skills & Qualifications:

• 8+ years of overall IT experience with 4+ years in Google Cloud Platform architecture.

• Strong hands-on experience with Google Cloud Platform services.

• Expertise in AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.

• Experience with Vertex AI, AutoML, BigQuery ML, or similar ML platforms.

• Strong understanding of data engineering concepts and real-time data processing.

• Experience in containerization (Docker) and orchestration (Kubernetes/GKE).

• Knowledge of Infrastructure as Code (Terraform/Deployment Manager).

• Strong programming skills in Python, Java, or Go.

• Experience implementing CI/CD pipelines for ML and cloud deployments.

• Understanding of cloud security best practices and compliance standards.

Preferred Qualifications

• Google Professional Cloud Architect Certification.

• Google Professional Machine Learning Engineer Certification.

• Experience with Generative AI, LLMs, or prompt engineering.

• Experience in hybrid/multi-cloud environments.

• Strong communication and stakeholder management skills.