Infrastructure Architect

Overview

As the Infrastructure Architect at Inception, you will play a pivotal role in architecting, developing, and optimizing infrastructure for Inception’s advanced AI platforms. With a robust background in cloud and on-premises infrastructure design, you’ll focus on ensuring the scalability, security, and high performance of our AI systems. Collaborating closely with engineering and operations teams, you’ll work to enhance the infrastructure that supports AI workloads, with an emphasis on cloud optimization, networking, and storage.

Inception, a G42 company, is the region’s leading innovator of AI-powered domain-specific as well as industry-agnostic products, built on a rich heritage of research and development. Within the G42 ecosystem, Inception functions as the core intelligence layer – transforming data and compute infrastructure into real-world, applied AI solutions. Beyond its commercial endeavors, Inception is committed to creating positive societal impact. For more information, please visit www.inceptionai.ai

Responsibilities

• Architect Infrastructure Solutions: Design and develop scalable, secure, and highly available infrastructure that supports Inception’s AI platforms and applications.
• Cloud & On-Premises Architecture: Develop cloud-based and on-premises infrastructure to meet AI/ML workload requirements for performance, scalability, and security.
• Collaboration with Key Teams: Work closely with engineering, DevOps, and product teams to optimize infrastructure for AI training, inference, and data processing.
• High Availability & Disaster Recovery: Build high availability and disaster recovery solutions to ensure the resilience of critical AI platforms.
• Networking Architecture: Design and implement robust networking solutions for secure and reliable connectivity across AI systems.
• Automation & Infrastructure as Code: Champion the use of automation and IaC, leveraging tools like Terraform, Ansible, and Kubernetes for streamlined infrastructure deployment and management.
• Cloud Efficiency & Cost Management: Implement best practices for cloud resource efficiency and cost-effectiveness while maintaining stringent security standards.
• Technology Evaluation & Integration: Continuously assess and integrate new technologies to enhance infrastructure capabilities in storage, networking, and cloud-native services.
• Compliance & Security: Ensure infrastructure adheres to regulatory and security requirements, focusing on data privacy, encryption, and access control.
• Technical Guidance: Provide mentorship and technical leadership to the infrastructure team, promoting best practices in infrastructure quality and efficiency.
• Industry Trends & Innovation: Stay current on industry advancements and drive infrastructure innovation to support evolving AI and technology trends.
  
  

• Experience: Minimum of 12 years in infrastructure architecture, cloud platforms, or systems engineering, with extensive experience in large-scale, mission-critical environments.
• Proven Cloud Expertise: Solid track record in architecting and managing infrastructures (AWS, Azure, GCP) for AI/ML workloads with a focus on scalability and resilience.
• Technical Proficiency: Expertise in cloud computing, networking, and storage, and experience with IaC tools like Terraform, Ansible, or CloudFormation.
• Containerization & Orchestration: Proficient in Docker and Kubernetes, with experience deploying and managing AI/ML workloads.
• Networking & Security Knowledge: Advanced understanding of networking protocols, VPNs, firewalls, and security best practices for hybrid and cloud environments.
• Storage Systems: Familiarity with storage solutions for AI/ML applications, including distributed storage and high-performance computing architectures.
• Resilience Strategies: Strong background in designing disaster recovery, business continuity, and high-availability plans.
• Cross-Functional Collaboration: Ability to work with DevOps, software engineering, and security teams to align infrastructure goals.
  
  

• Experience: Minimum of 12 years in infrastructure architecture, cloud platforms, or systems engineering, with extensive experience in large-scale, mission-critical environments.
• Proven Cloud Expertise: Solid track record in architecting and managing infrastructures (AWS, Azure, GCP) for AI/ML workloads with a focus on scalability and resilience.
• Technical Proficiency: Expertise in cloud computing, networking, and storage, and experience with IaC tools like Terraform, Ansible, or CloudFormation.
• Containerization & Orchestration: Proficient in Docker and Kubernetes, with experience deploying and managing AI/ML workloads.
• Networking & Security Knowledge: Advanced understanding of networking protocols, VPNs, firewalls, and security best practices for hybrid and cloud environments.
• Storage Systems: Familiarity with storage solutions for AI/ML applications, including distributed storage and high-performance computing architectures.
• Resilience Strategies: Strong background in designing disaster recovery, business continuity, and high-availability plans.
• Cross-Functional Collaboration: Ability to work with DevOps, software engineering, and security teams to align infrastructure goals.