Principal Ai Engineer - Cloud Infrastructure

About the Role
Our client, a highly innovative company operating at the forefront of AI & Emerging Technologies, is seeking an exceptional Principal AI Engineer to spearhead the development and optimization of their cloud infrastructure. This senior role is critical for designing, building, and maintaining the scalable, robust, and efficient cloud environments that power our cutting-edge AI research and development efforts. You will be instrumental in shaping the future of our AI platform, ensuring its reliability, security, and performance. This is a fully remote position, offering the ultimate flexibility to work from anywhere in the world and collaborate with a globally distributed team of top-tier AI professionals. We are looking for a seasoned engineer with a deep understanding of cloud architecture, MLOps, and infrastructure automation, who is passionate about enabling breakthroughs in artificial intelligence. This role offers the opportunity to lead significant technical initiatives and make a lasting impact on our client's technological foundation.Key Responsibilities
Architect, implement, and manage scalable, secure, and highly available cloud infrastructure (AWS, Azure, or GCP) for AI/ML workloads.Develop and maintain robust CI/CD pipelines for automated deployment of AI models and infrastructure.Implement infrastructure as code (IaC) solutions using tools like Terraform or CloudFormation.Optimize cloud resource utilization and costs for AI training and inference at scale.Design and manage containerization platforms (Docker, Kubernetes) for AI applications.Ensure the security and compliance of cloud environments, adhering to best practices and regulatory requirements.Collaborate closely with AI researchers, data scientists, and ML engineers to understand their infrastructure needs and provide solutions.Develop monitoring, logging, and alerting strategies for AI systems and infrastructure.Troubleshoot and resolve complex infrastructure issues, ensuring minimal downtime.Lead the adoption of new cloud technologies and MLOps best practices.Mentor junior engineers and contribute to the technical growth of the team.Requirements
Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.10+ years of experience in software engineering and infrastructure management, with at least 5 years focused on cloud infrastructure for AI/ML.Deep expertise in at least one major cloud platform (AWS, Azure, GCP) and its AI/ML services.Proven experience with infrastructure as code (IaC) tools (Terraform, Ansible, CloudFormation).Strong proficiency in containerization technologies (Docker, Kubernetes) and orchestration.Extensive experience with CI/CD tools and methodologies.Solid understanding of networking, security, and data storage principles in a cloud context.Proficiency in scripting languages such as Python or Bash.Experience with MLOps practices and tools for model deployment and lifecycle management.Excellent problem-solving, analytical, and communication skills, essential for remote collaboration.Proven ability to lead complex technical projects and mentor team members.Experience with monitoring and logging tools (e.G., Prometheus, Grafana, ELK stack).Benefits
Executive-level compensation package including base salary, bonus, and equity options.Full remote work flexibility with comprehensive home office support.Premium health, dental, and vision insurance coverage.Generous paid time off and flexible working arrangements.Significant budget for professional development, conferences, and training.Opportunity to work with groundbreaking AI technologies and shape the future of AI infrastructure.Lead a team of highly skilled engineers in a cutting-edge, collaborative environment.Contribute to projects with massive scale and global impact from anywhere.
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