Cloud Infrastructure Architect

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Job Description

Description

Key Responsibilities :

Cloud Architecture & Strategy

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.

MLOps & AI/ML Enablement

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.

Data Consolidation & Platform Integration

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.

Security, Compliance & Governance

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.

Technical Leadership & Collaboration

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.

Performance Monitoring & Optimization

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.

Technical Skills & Competencies

Core Skills :

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.

Tools & Platforms

Cloud Platforms :