Location : Bangalore (Hybrid)

Exp : 5+ years

What will you do :

- Design and implement AI Agents to optimize cloud resource allocation, auto-scaling, and performance tuning.

- Develop predictive models for failure detection, incident management, and system health monitoring.

- Automate operational workflows using machine learning and intelligent scripting.

- Integrate AI-driven insights with existing cloud monitoring tools.

- Collaborate with DevOps and SRE teams to deploy, monitor, and improve ML models in production environments.

- Conduct anomaly detection for security, cost optimization, and performance analytics.

- Continuously evaluate emerging AI technologies and tools for operational improvements.

- Maintain documentation and best practices for AI/ML integration in cloud systems.

Our Minimum Requirements include :

- Bachelor's or equivalent experience or Masters degree in Computer Science, Data Science, or related technical field.

- Proven ability building and deploying ML models, with at least 2 years focused on infrastructure or cloud operations.

- Solid knowledge of hybrid cloud technologies (AWS, GCP, OpenStack, Kubernetes).

- Experience with Python, Jupiter, and ML libraries such as PyTorch, TensorFlow, or scikit-learn.

- Familiarity with cloud-native monitoring, logging, and automation tools (e.g., Terraform, Ansible, Prometheus, Splunk, AppDynamics).

- Comfortable working with streaming data, APIs, and telemetry systems.

- Strong communication and multi-functional collaboration skills.

- Experience with Agile and DevOps operating models, including project tracking tools (e.g., Jira), Git (any Version Control systems), and CI/CD systems (e.g., GitLab, GitHub Actions, Jenkins).

- Proficient in general-purpose programming languages (Python, GoLang, Bash and/or C/C++) and development platforms and technologies.