Principal SaaS Capacity Engineer

Required Qualifications

• Bachelors or Masters degree in Computer Science Electrical Engineering Cloud/Systems Engineering or a related field.
• 5 years of experience in cloud infrastructure SaaS operations or capacity engineering roles.
• Hands-on experience with large-scale distributed systems OCI (or AWS Azure GCP) and SaaS production environments.
• Strong programming and scripting experience (Python Go Shell SQL) for automation and AI/ML model deployment.
• Proven experience deploying AI/ML solutions for capacity forecasting anomaly detection and intelligent workload tuning.
• Deep understanding of cloud capacity topology and distributed service dependencies.
• Proficiency with infrastructure-as-code (Terraform Ansible Helm Kubernetes).
• Familiarity with AIOps tools and AI-driven observability platforms (Datadog Dynatrace Splunk or similar).
• Knowledge of resiliency and disaster recovery strategies including AI-simulated failure modeling.

Preferred Qualifications

• Advanced degree (Masters/PhD) with specialization in AI ML Data Science or distributed systems engineering.
• Experience building and deploying self-healing AI-driven automation at scale in a SaaS environment.
• Domain expertise in reinforcement learning applications for automated resource optimization.
• Direct exposure to Oracle Cloud Infrastructure (OCI) systems and tools.
• Experience with cloud-native AI/ML services MLOps and continuous model monitoring.

Competencies and Skills

• Expertise in designing developing and deploying AI/ML models for cloud infrastructure use cases (demand forecasting anomaly detection workload optimization).
• Advanced proficiency in automation orchestration and self-healing system architectures.
• Skilled in communicating technical concepts AI-powered analytics and strategic insights to engineering and executive audiences.
• Strong analytical and critical thinking skills with a deep data-driven mindset.
• Curiosity and initiative to explore APIs system profiles and operational anomalies translating technical findings into impactful business outcomes.
• Highly collaborative adaptive and passionate about operational excellence and continuous learning.
• Ability to influence cross-team priorities and drive best practices in AI-enhanced capacity engineering.

Key Responsibilities

• Service Accountability: Ensure SaaS production capacity availability optimization scaling automation reserve management and quota governance.
• AI/ML Integration: Apply AI/ML models for predictive capacity forecasting anomaly detection and workload auto-tuning to anticipate demand spikes and prevent outages.
• Observability & AIOps: Leverage AI-powered observability and AIOps platforms for end-to-end system monitoring intelligent alerting and automated incident mitigation.
• Strategic Partnership: Collaborate with Product and Development teams to design validate and align AI-driven scaling and capacity planning strategies with new launches and initiatives.
• Automation & Orchestration: Design implement and optimize automation and orchestration pipelines including self-healing systems policy-driven provisioning and disaster recovery simulations using AI to enhance reliability and operational resilience.
• Data-Driven Decision Support: Deliver advanced instrumentation AI-powered analytics and actionable dashboards to inform executives engineering teams and stakeholders.
• Technical Leadership: Translate complex OCI stack and cloud platform resources (compute storage DB networking) into business-ready AI-enhanced capacity solutions and performance profiles.
• Simulation & Resiliency: Use AI/ML models to simulate validate and improve resiliency and disaster recovery scenarios for faster more robust recovery response.
• Collaboration & Communication: Present AI-driven insights risks and recommendations to engineering teams ICs and executives to illuminate capacity trends and data-driven priorities.
• Continuous Innovation: Assess new AI/ML techniques AIOps platforms and automation tools for ongoing improvements in infrastructure reliability scalability and cost optimization.

Career Level - IC4