Google Cloud Solutions Engineer

Job Description

Job Overview Google Cloud Solutions Engineer:

We are seeking an experienced and hands-on Google Cloud Solutions Engineer to join our team as we scale our AI and machine learning initiatives on Google Cloud Platform. This role requires deep technical expertise in configuring, deploying, and optimizing GCP services, ensuring our cloud infrastructure is robust, scalable, and efficient.

As a key cloud expert, you will be responsible for architecting and implementing critical cloud services, including networking, security, storage, compute, and AI/ML integrations. The ideal candidate will have extensive hands-on experience with GCP service setup, automation, and best practices to support our AI-driven workloads.

This role will also serve as a strategic advisor, guiding the team in adopting the right GCP tools, services, and architectures while ensuring cost efficiency and security. If you're a Google Cloud expert who thrives on building scalable solutions and enabling high-impact AI/ML projects, this is an opportunity to play a pivotal role in shaping our cloud journey.

Key Responsibilities

• Google Cloud Expertise:
• Assess project requirements and recommend the best GCP services (e.g., Compute Engine, GKE, Cloud Storage, BigQuery) for our ML/AI workloads and beyond.
• Design and configure scalable, secure, and cost-effective cloud architectures tailored to our needs.
• Guide the team on provisioning resources, setting up networking (VPCs, load balancers), and managing data storage and pipelines.
• Optimize cloud usage with tools like Cloud Billing, Recommenders, and cost management strategies.
• Troubleshoot and resolve cloud-related issues to ensure smooth operations.

• AI Services Support:
• Provide insights into Google Cloud AI services (e.g., Vertex AI, AutoML, BigQuery ML) to support our ML/AI engineers.
• Assist in integrating AI models into GCP infrastructure using APIs, SDKs, or serverless options like Cloud Functions.
• Collaborate with our ML/AI team to ensure cloud setups align with model training, deployment, and inference needs.

• Team Enablement:
• Educate and mentor our team on Google Cloud best practices, service selection, and basic administration.
• Document cloud architectures, configurations, and decision-making processes for team reference.
• Act as a liaison between technical teams to align cloud strategies with project goals.

• Security & Compliance:
• Implement security controls using IAM, Secret Manager, and Cloud KMS to protect cloud resources.
• Advice on compliance requirements (e.g., GDPR, HIPAA) for data handling in the cloud.

Required Qualifications

• Experience:
• 6+ years of hands-on experience with Google Cloud Platform, including architecture design and service configuration.
• Proven ability to guide teams new to cloud platforms in adopting and leveraging services effectively.
• 1-2 years of exposure to Google Cloud AI services (e.g., Vertex AI, AI Platform) in a support or integration capacity.

• Technical Skills:
• Deep knowledge of GCP core services: Compute Engine, GKE, Cloud Storage, BigQuery, Cloud Functions, and networking.
• Expertise in cloud resource management, cost optimization, and scalability planning.
• Strong understanding of data pipelines (e.g., Dataflow, Pub/Sub) and storage solutions for ML/AI workloads.
• Familiarity with Google Cloud AI tools and their integration into applications (e.g., APIs, serverless setups).
• Basic programming/scripting skills (e.g., Python, Java script) for automation or configuration tasks.

• Certifications (Preferred):
• Google Cloud Professional Cloud Architect (highly desired).
• Google Cloud Professional Data Engineer or Machine Learning Engineer (optional but beneficial).

Preferred Qualifications

• Experience onboarding teams or organizations to Google Cloud from scratch.
• Familiarity with hybrid/multi-cloud setups or migrations.
• Exposure to frontend/backend integration with GCP services (e.g., APIs, App Engine).
• Knowledge of ML/AI workflows (e.g., model training, inference) to better support the team.

Job Classification

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