Site Reliability Engineer (SRE)

We are looking for a Site Reliability Engineer (SRE) to join Lucidya Cloud Engineering team and contribute to improving the reliability, scalability, and automation of our cloud-based infrastructure. The ideal candidate will have hands-on experience with cloud environments, containerized workloads, automation tools, and monitoring systems, as well as a proactive mindset for enhancing system availability and performance.

Key Responsibilities:

1. Infrastructure Reliability
   
   

• Ensure high availability (HA) and scalability of critical infrastructure components (e.g., Redis, RabbitMQ, Kubernetes clusters).
• Proactively identify and eliminate single points of failure across the cloud environment.
• Linux Systems Administration: Handle infrastructure management tasks such as patching, performance tuning, and monitoring of Linux-based systems.

• Manage and optimize cloud-based workloads across AWS, GCP, or Azure.
• Automate provisioning, scaling, and maintenance tasks using Infrastructure as Code (IaC) tools such as Terraform, AWS CloudFormation, or similar.

• Manage the day-to-day operations of Kubernetes clusters, including deployment, scaling, upgrades, and troubleshooting.

• Implement and standardize monitoring solutions using tools like Datadog, Prometheus, or Grafana to track golden metrics and improve alerting systems.
• Participate in on-call rotations, troubleshoot incidents, and drive post-incident reviews to implement lasting solutions.

• Develop and maintain automation scripts for routine operational tasks to reduce manual efforts and increase efficiency.
• Advocate for AWX/Ansible adoption to automate configurations and deployments.

• Work closely with DevOps and Engineering teams to identify and resolve performance bottlenecks.
• Contribute to the establishment of best practices for infrastructure and application reliability.

Key Requirements:

1. Experience and Knowledge
   
   

• ~ 3 years of experience in a similar SRE, DevOps, or Infrastructure Engineer role.
• Strong experience with at least one major cloud provider (AWS, GCP, or Azure).
• Hands-on experience with Kubernetes and containerization (e.g., Docker).

• Proficient in scripting languages such as Python, Bash, or similar for automation.
• Familiarity with Infrastructure as Code (IaC) tools like Terraform, Pulumi, or AWS CloudFormation.
• Strong understanding of load balancers, networking (IP management, subnetting), and HA architecture.
• Experience with CI/CD tools (e.g., Bitbucket Pipelines, Jenkins, GitHub Actions).

• Experience with modern monitoring and observability tools (e.g., Datadog, ELK, Grafana).
• Ability to define and track golden metrics and establish meaningful alerting thresholds.

• Strong analytical skills and ability to resolve complex technical issues.
• Proven track record in root cause analysis and incident management.

• Excellent communication and collaboration skills to work across teams.
• Self-motivated and proactive in improving systems and processes.