7 Madhees Jobs

Director SRE for the Partner Company into Product Development. Looking for someone who worked on end to end SRE with Devops.

Qualifications :

- Bachelors or Masters degree in Computer Science, Data Engineering, AI/ML, or a related field.

- 10+ years of experience in software release management, with at least 3-5 years in SRE or DevOps environments, preferably in AI or data-driven applications.

- Proven experience building and managing both release management and SRE teams in complex, multi product environments.

- Strong knowledge of AI/ML operations (MLOps), data pipeline management, and cloud-based AI product deployments.

- Expertise in release management tools (Jenkins, GitLab, Git, Jira) and SRE tools such as Prometheus, Grafana, Datadog, or similar monitoring systems.

- Experience with cloud platforms (AWS, GCP, Azure), containerization (Kubernetes, Docker), and infrastructure automation tools (Terraform, Ansible).

- Excellent problem-solving, organizational, and leadership skills, with a strong track record of driving continuous improvement in both release and operational reliability processes.

Preferred Qualifications :

- Experience deploying and maintaining large-scale AI/ML models in production environments, including monitoring, retraining, and operationalization.

- Familiarity with ITIL, MLOps, or DevOps frameworks and best practices.

- Knowledge of cloud-based services and tools specifically designed for AI/ML (e.g., AWS SageMaker, TensorFlow, PyTorch).

- Demonstrated ability to manage incident response and root cause analysis in complex software ecosystems.

Responsibilities :

- Build, mentor, and lead a high-performing SRE and release management team.

- Foster a culture of ownership, collaboration, and continuous improvement.

- Define team goals, performance metrics, and career development plans.

- Develop and implement SRE best practices, including monitoring, alerting, capacity planning, and incident response.

- Ensure the reliability, availability, and performance of our production systems.

- Drive the adoption of automation and infrastructure-as-code principles.

- Establish and maintain service level objectives (SLOs) and service level agreements (SLAs).

- Oversee the end-to-end release management process, ensuring smooth and efficient deployments.

- Implement and maintain CI/CD pipelines using tools like Jenkins, GitLab, and Git.

- Promote DevOps principles and practices across the organization.

- Manage and optimize data pipelines and MLOps workflows.

- Manage and optimize cloud infrastructure on platforms like AWS, GCP, or Azure.

- Implement and manage containerization and orchestration using Kubernetes and Docker.

- Utilize infrastructure automation tools like Terraform and Ansible to ensure consistent and scalable deployments.

- Oversee the monitoring and management of large-scale AI/ML models in production.

- Lead incident response and root cause analysis efforts.

- Implement proactive monitoring and alerting systems using tools like Prometheus, Grafana, and Datadog.

- Develop and maintain incident response playbooks and procedures.

- Improve system resilience, and minimize downtime.

- Collaborate with development, product, and data science teams to ensure alignment on reliability and release goals.

- Communicate effectively with stakeholders at all levels of the organization.

- Document processes, procedures, and best practices.