Wand Synthesis AI Inc - Senior Site Reliability Engineer
Requirements
• Strong hands-on experience in Site Reliability Engineering, DevOps roles. • Experience working with cloud infrastructure (AWS preferred). • Experience operating production systems and responding to incidents. • Experience with Kubernetes in production environments. • Strong experience with Infrastructure-as-Code (Terraform or similar). • Experience working with CI/CD pipelines and deployment automation. • Experience with monitoring, logging, and observability tooling. • Strong troubleshooting and debugging skills in distributed systems. • Experience supporting data platforms or ML workloads in production environments. • Strong collaboration and communication skills. • Experience in large-scale global B2B/B2C products. • Experience working with AI, ML, or data-intensive systems. • Exposure to MLOps workflows (model deployment, monitoring, retraining). • Experience supporting customer-hosted or multi-tenant environments. • Experience working in regulated or security-conscious environments. • Experience scaling infrastructure in high-growth product environments. • Experience in collaborating with large scale enterprise customers to deploy and operate environments within their accounts and VPCs. • Personal Characteristics • Strong sense of ownership and accountability for systems in production. • Practical and hands-on approach to solving operational problems. • Calm and methodical during incidents and troubleshooting situations. • Strong collaborator who works effectively across engineering teams. • Curious and eager to continuously improve systems and processes. • Bias toward automation and reducing manual operational work. • Comfortable working in fast-moving, evolving technical environments.
Responsibilities
• Build, maintain, and operate scalable production infrastructure. • Own reliability and availability for key services and environments. • Contribute to the design and operation of Kubernetes-based infrastructure. • Develop and maintain Infrastructure-as-Code frameworks (e.g., Terraform). • Improve monitoring, alerting, and observability across systems. • Participate in on-call rotations and respond to production incidents. • Investigate root causes of incidents and contribute to postmortems and reliability improvements. • Improve system performance, availability, and fault tolerance. • Contribute to CI/CD pipeline improvements to increase release safety and predictability. • Support the deployment and operation of data platforms and ML workloads. • Help standardise environments and infrastructure across internal systems and customer deployments. • Troubleshoot issues across infrastructure, services, and deployment pipelines. • Work closely with QA and engineering teams to improve production readiness and release stability. • Contribute to automation efforts that reduce operational toil.
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