Site Reliability Engineer

we have open requirement for "SRE LEAD Engineer"

client: MNC.

PRODUSCT BASE US COMPANY

Role & responsibilities

Responsibilities:

• 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.

Qualifications :

• 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.

Preferred candidate profile

If interested candidates please share the your profiles to HR@TECHXLNC.AI

NP: Immediate to 30 days

loc:HYD