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GCP Cloud Architect

Job in Springfield, Greene County, Missouri, 65897, USA
Listing for: AI Technologies LLC.
Full Time position
Listed on 2025-12-27
Job specializations:
  • IT/Tech
    Cloud Computing
Salary/Wage Range or Industry Benchmark: 100000 - 130000 USD Yearly USD 100000.00 130000.00 YEAR
Job Description & How to Apply Below

Job Description

Responsibilities
  • Design and implement robust cloud architectures on Google Cloud Platform (GCP).
  • Lead the cloud foundation build, ensuring best practices in security, scalability, and performance.
  • Manage and execute the migration of on‑premises infrastructure to GCP.
  • Implement and optimize Vertex AI solutions for advanced machine learning and AI capabilities.
  • Collaborate with cross‑functional teams to understand business requirements and translate them into technical solutions.
  • Provide technical leadership and mentorship to junior engineers and architects.
  • Ensure compliance with industry standards and regulatory requirements.
  • Troubleshoot and resolve complex technical issues related to GCP infrastructure and services.
  • Stay updated with the latest GCP features, tools, and best practices.
Qualifications
  • Bachelor's or Master’s degree in Computer Science, Information Technology, or a related field.
  • Minimum of 5 years of hands‑on experience with GCP architecture and services.
  • Proven experience in cloud foundation build and on‑premises to GCP migration projects.
  • Strong expertise in Vertex AI and implementing machine learning models on GCP.
  • Proficiency in GCP services such as Compute Engine, Cloud Storage, Big Query, Cloud Functions, and Kubernetes Engine.
  • Excellent understanding of networking, security, and IAM in GCP.
  • Strong problem‑solving skills and the ability to work in a fast‑paced environment.
  • Excellent communication and collaboration skills.
Technical Skills Required
  • Experience with Terraform, Ansible, or other infrastructure‑as‑code (IaC) tools.
  • Knowledge of Dev Ops practices and CI/CD pipelines.
  • Proficiency in scripting languages such as Python, Bash, or Power Shell.
  • Experience with containerization technologies like Docker and orchestration tools like Kubernetes.
  • Familiarity with monitoring and logging tools such as Stackdriver, Prometheus, and Grafana.
  • Understanding of data engineering concepts and tools like Dataflow, Dataproc, and Pub/Sub.
  • Experience with API management and microservices architecture.
  • Knowledge of security best practices, including encryption, key management, and identity management.
  • Familiarity with other cloud platforms like AWS or Azure.
  • Experience with cloud‑native application development and serverless architectures.
  • Proficiency in designing and implementing disaster recovery and business continuity plans.
  • Knowledge of cloud cost management and optimization strategies.
  • Experience with hybrid cloud environments and multi‑cloud strategies.
  • Familiarity with cloud compliance frameworks such as GDPR, HIPAA, and SOC 2.
  • Proficiency in using GCP’s AI and machine‑learning tools, such as AutoML and AI Platform.
  • Experience with data warehousing solutions like Big Query and data lake architectures.
  • Knowledge of cloud networking concepts, including VPC, VPN, and interconnects.
Preferred Skills
  • GCP Professional Cloud Architect certification.
  • Experience with hybrid cloud environments and multi‑cloud strategies.
  • Knowledge of machine‑learning frameworks such as Tensor Flow, PyTorch, or scikit‑learn.
  • Experience with serverless computing and event‑driven architectures.
Key Performance Indicators (KPIs)
  • Cloud Infrastructure Uptime: measure the availability and reliability of the cloud infrastructure.
  • Cost Optimization: track cloud spending and identify opportunities for cost savings.
  • Migration Success Rate: evaluate the success of on‑premises to GCP migration projects.
  • Performance Metrics: monitor application response times, latency, and throughput.
  • Security Compliance: ensure the cloud environment adheres to security best practices and compliance requirements.
  • Scalability and Flexibility: measure the ability to scale resources up or down based on demand.
  • Incident Response Time: track time taken to detect, respond to, and resolve incidents.
  • User Satisfaction: gather feedback from stakeholders and end‑users to assess satisfaction with cloud solutions.
  • Innovation and Improvement: measure the frequency and impact of new features and optimizations introduced.
  • Training and Development: track ongoing training and certification of the cloud team.

Equal Opportunity Employer

AI TECHNOLOGIES LLC is an equal opportunity…

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