Principal AI Cloud Systems Engineer

Essential Duties And Responsibilities

• Work with other engineering leaders to establish and implement cloud engineering requirements and standards across AWS and Azure.
• Help define, evolve, and approve architectural standards for cloud infrastructure, networking, security, identity, and platform services.
• Design and deliver highly available, fault-tolerant, and scalable cloud platforms supporting transactional, data, and AI/ML workloads.
• Drive end-to-end automation using Infrastructure as Code practices.
• Lead multi-account / multi-subscription cloud landing zone design, including networking, identity, governance, and security baselines.
• Architect and guide CI/CD pipelines integrating application, infrastructure, and data deployments.
• Partner with AI COE teams to enable cloud platforms for AI/ML, GenAI, MLOps, data pipelines, and experimentation environments.
• Collaborate with product, SRE, security, data, and operations teams in an agile delivery model.
• Lead the design and improvement of monitoring, logging, alerting, and observability platforms.
• Apply Site Reliability Engineering (SRE) principles including SLOs, SLIs, error budgets, and resilience testing.
• Influence platform roadmaps, advocate for new cloud-native services, and assess emerging technologies.
• Mentor and coach cloud and systems engineers throughout the full development lifecycle.
• Act as a senior technical advisor across multiple initiatives and platforms.
• Ensure solutions meet functional, non-functional, security, compliance, and financial requirements.
• Champion continuous improvement, innovation, and operational excellence.
• Maintain strong documentation, knowledge sharing, and design review practices.

Required Qualifications

• Minimum of 10+ years of experience in systems and cloud engineering with deep hands-on expertise.
• Strong experience designing and operating production environments in both AWS and Microsoft Azure.
• Proven expertise with Infrastructure as Code: Terraform (preferred), AWS CloudFormation, Azure Bicep / ARM.
• Proficiency in programming and scripting languages commonly used in cloud engineering, such as Python, PowerShell, Bash, or Go.
• Demonstrated experience building and operating CI/CD pipelines using tools such as GitHub Actions, Azure DevOps, Jenkins, or similar.
• Advanced knowledge of cloud networking (VPC/VNet, routing, load balancing, DNS, hybrid connectivity).
• Strong background in cloud security including IAM, network security, encryption, secrets management, and zero-trust principles.
• Experience supporting containerized and cloud-native platforms (Kubernetes/EKS/AKS, managed PaaS services).
• Experience enabling data, analytics, and AI/ML platforms in the cloud.
• Deep understanding of Linux and Windows server platforms.
• Strong grasp of the Software Development Lifecycle (SDLC) and agile delivery models.
• Excellent communication skills with the ability to influence across all levels of the organization.
• Demonstrated ability to work effectively in an agile, cross-functional AI COE environment.

Preferred Qualifications

• Experience with MLOps, model deployment pipelines, or AI platform operations.
• Experience with multi-cloud cost management and FinOps practices.
• Industry certifications such as AWS Solutions Architect (Professional), Azure Solutions Architect Expert, or equivalent.
• Experience with enterprise governance frameworks and regulated environments.