Lead Site Reliability Engineer
4 weeks ago
We have an exclusive job role as below :
Lead Site Reliability Engineer (SRE) | Hyderabad (WFO) | 8-12 Yrs |
Scope Of Work :
- Architect, design, and deploy end-to-end infrastructure solutions for a multi-tenant microservices-based SaaS application with a focus on AI/ML model integration.
- Ensure system reliability, scalability, performance, and security, specifically enhancing AI/ML processing pipelines and workflows.
- Utilize Terraform scripting for on-demand environment provisioning within the AWS cloud, optimized for AI/ML workloads.
- Implement and refine monitoring and alerting systems across application, network, and OS layers to support AI model operations and data processing.
- Diagnose, support, and resolve production issues and alerts, participating in a 24/7 on-call rotation to maintain seamless AI/ML service operations.
Experience Required :
- 8+ years of experience in Site Reliability Engineering (SRE) and DevOps roles with a track record of managing large-scale enterprise SaaS services in production, including 1+ year in AI/ML infrastructure.
- Demonstrated expertise with AWS public cloud technologies, including extensive experience in deploying and managing large-scale container clusters using AWS, EKS.
- Skilled in Infrastructure as Code (IaC) using Terraform, and container technologies such as Docker and Kubernetes.
- Proficient in scripting and programming for automation (Python, Bash, etc.), with strong Linux OS and networking fundamentals relevant to AI/ML workloads.
- Experience in establishing monitoring systems to ensure high availability, performance, and security integrity, using tools like ELK Stack, CloudWatch, and others tailored for AI/ML monitoring.
- Hands-on experience managing microservices architecture SaaS products, enabling RESTful web services, SSO integration (Okta, Auth0), and utilizing cloud databases like EC2-RDS, MySQL, and Elasticsearch, especially in AI/ML deployments.
- Proficient in backup and disaster recovery strategies specific to AI/ML data resources like RDS and Elasticsearch.
- AWS Certified Solutions Architect is strongly preferred.
- Self-driven, proactive, and adaptable to thrive in an early-stage startup environment, with a keen interest in integrating AI/ML technologies into modern SaaS solutions.
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