Cloud Infrastructure Architect

Overview

• Design and implement end-to-end cloud architectures (IaaS, PaaS, SaaS) across multiple platforms (AWS, Azure, GCP).
• Define cloud adoption strategies, migration plans, and reference architectures aligned with business objectives.
• Lead cloud transformation initiatives, ensuring scalability, security, and operational efficiency.
• Provide guidance on hybrid and multi-cloud strategies, integrating on-premises and cloud infrastructure.
  
  

• Design and implement MLOps pipelines to enable AI/ML model deployment, monitoring, and lifecycle management.
• Work with data science and engineering teams to integrate AI/ML workloads with cloud infrastructure.
• Ensure automation, reproducibility, and scalability of ML workflows and model serving platforms.
  
  

• Architect solutions for data consolidation, data lakes, and data warehouses.
• Ensure integration of structured and unstructured data across enterprise systems.
• Collaborate with analytics and business intelligence teams to enable data-driven decision-making.
• Design high-performance, resilient, and secure data pipelines and storage solutions.
  
  

• Implement cloud security best practices, including identity management, encryption, network security, and compliance controls.
• Ensure adherence to industry standards (ISO, SOC2, GDPR, HIPAA as applicable).
• Define governance models, monitoring frameworks, and operational policies.
  
  

• Provide technical leadership to cloud, DevOps, and infrastructure teams.
• Review architecture designs, guide implementation, and ensure best practices.
• Collaborate with product, engineering, and data teams to ensure alignment with business requirements.
• Evaluate emerging cloud technologies, tools, and frameworks for adoption.
  
  

• Establish KPIs and monitoring frameworks for cloud infrastructure and MLOps workflows.
• Optimize cloud resource utilization, cost efficiency, and performance.
• Lead incident resolution and root cause analysis for cloud infrastructure issues.
  
  

• Strong expertise in IaaS, PaaS, SaaS architectures and multi-cloud environments.
• Hands-on experience with AWS, Azure, GCP, and hybrid cloud solutions.
• Deep understanding of MLOps frameworks (Kubeflow, MLflow, SageMaker, Azure ML).
• Expertise in data consolidation, data lakes, data warehouses, and cloud-native storage solutions.
• Experience with automation and IaC using Terraform, Ansible, or CloudFormation.
• Knowledge of containerization (Docker, Kubernetes) and microservices architectures.
• Strong grasp of networking, security, identity management, and compliance in cloud environments.
  
  

• AWS, Azure, GCP
  
  

• Kubeflow, MLflow, SageMaker, Azure ML, TensorFlow Serving
  
  

• Snowflake, Redshift, BigQuery, Databricks, Hadoop ecosystem
  
  

• Terraform, Ansible, Jenkins, GitLab CI/CD, ArgoCD
  
  

• Prometheus, Grafana, ELK, CloudWatch
  
  

(ref:hirist.tech)