Senior Site Reliability Engineer

• Own and drive AWS cost optimization and efficiency initiatives across ThousandEyes infrastructure.
• Analyze cloud usage across compute, storage, databases, observability, networking, and data platform workloads to identify savings opportunities.
• Partner with engineering teams to improve application and infrastructure performance while reducing cloud wastage.
• Drive FinOps practices including cost visibility, tagging hygiene, showback/chargeback, budgeting, forecasting, anomaly detection, and cost allocation.
• Improve infrastructure efficiency through better resource utilization, autoscaling, right-sizing, and capacity planning.
• Build automation, dashboards, reports, and guardrails to improve cost governance and operational visibility.
• Support ThousandEyes cost reviews, OKR tracking, leadership updates, and stakeholder communications.
• Collaborate with product, finance, engineering, and platform teams to align cost optimization with business priorities.
• Identify and reduce underutilized infrastructure, idle resources, over-provisioned workloads, and inefficient service usage.
• Improve observability, alerting, and monitoring for cost, performance, and platform health indicators.
• Influence engineering teams to adopt cost-aware architecture, reliable design patterns, and performance-efficient implementation practices.
• Provide senior-level technical leadership, mentor engineers, and independently drive cross-functional initiatives to closure.
• Balance reliability, scalability, performance, and cost efficiency in all platform decisions.

• Bachelor’s degree or higher in Engineering, Computer Science, or equivalent practical experience.
• 8–12 years of relevant experience in Site Reliability Engineering, Cloud Infrastructure, Platform Engineering, DevOps, Production Engineering, or Performance Engineering.
• Strong experience with AWS services such as EC2, S3, RDS, EMR, Lambda, CloudWatch, OpenSearch, ElastiCache, IAM, VPC, and related cloud-native services.
• Practical experience in cloud cost optimization, FinOps, AWS billing analysis, cost allocation, tagging, budget tracking, forecasting, and cost governance.
• Experience with performance analysis, capacity planning, infrastructure optimization, and reliability improvements for large-scale cloud platforms.
• Experience with infrastructure-as-code and automation tools such as Terraform, CloudFormation, Puppet, Ansible, or similar.
• Strong scripting or programming skills in Python, Go, Shell, or similar languages for automation, reporting, and operational tooling.
• Experience with observability and monitoring platforms such as ThousandEyes, CloudWatch, Prometheus, Grafana, Splunk, OpenSearch, Datadog, or similar.
• Strong Linux systems knowledge and understanding of distributed systems.
• Experience in incident management, production support, reliability engineering, and operational excellence.
• Ability to analyze large-scale infrastructure, performance, and cost data and convert findings into actionable engineering recommendations.
• Strong communication skills with the ability to present technical, performance, and cost insights to engineering teams, finance, leadership, and multi-functional stakeholders.
• Experience working in Agile/Scrum environments and managing priorities across multiple teams.

• Experience supporting or optimizing large-scale SaaS platforms in AWS.
• FinOps certification or equivalent experience with cloud financial management practices.
• Experience with AWS Savings Plans, Reserved Instances, Spot adoption, Graviton migration, storage lifecycle optimization, workload right-sizing, and commitment planning.
• Experience with cloud cost management tools such as AWS Cost Explorer, AWS CUR, Cloud-ability, Cloud-Health, or similar platforms.
• Experience with performance tuning of cloud infrastructure, distributed systems, databases, data pipelines, and high-scale services.
• Experience with data platforms or large-scale infrastructure components such as EMR, Kafka, OpenSearch, RDS, Airflow, Spark, Redis, Cassandra, or similar.
• Experience driving cross-team cost optimization programs, efficiency OKRs, governance reviews, executive reporting, and measurable savings outcomes.
• Ability to influence engineering teams toward cost-conscious architecture, performance-aware design, and operational standard methodologies.
• Exposure to AI/ML infrastructure cost optimization, capacity planning, GPU/accelerator cost governance, or AI-driven efficiency tooling is a plus.

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