AI Ops Engineer

Deloitte India-- F2F Drive in Bangalore ,Delhi(NCR) and Chennai on 13th December

About the Role

We are looking for an AIOps Engineer to design and maintain intelligent operations systems that leverage AI/ML to optimize IT performance, detect anomalies, and automate incident response. This role combines expertise in IT operations with a strong understanding of machine learning to build scalable, resilient, and proactive monitoring and remediation frameworks.

As an AIOps Engineer, you will help transform traditional operations through automation, observability, and predictive analyticsreducing downtime and increasing system efficiency across complex environments.

Key Responsibilities

• Implement and maintain AI-driven systems for real-time monitoring, alerting, anomaly detection, and root cause analysis
• Develop and train machine learning models using operational data (logs, metrics, events, traces)
• Automate incident detection and remediation workflows (e.g., self-healing scripts, intelligent runbooks)
• Collaborate with DevOps, SRE, and IT teams to integrate AIOps tools into CI/CD pipelines and cloud infrastructure
• Design data pipelines that ingest, clean, and analyze high-volume system telemetry data
• Evaluate and deploy AIOps platforms (e.g., Moogsoft, Dynatrace, Splunk, BigPanda, DataDog, Elastic)
• Monitor model performance, manage retraining cycles, and ensure AI reliability

Qualifications

• Bachelors or Masters degree in Computer Science, IT, Data Science, or related field
• Experience in DevOps, SRE, or infrastructure automation roles
• Proficiency in Python, Bash, or other scripting languages
• Familiarity with AI/ML frameworks (e.g., Scikit-learn, TensorFlow, PyTorch)
• Strong understanding of observability stacks (e.g., Prometheus, Grafana, ELK, OpenTelemetry)
• Experience with public cloud platforms (AWS, Azure, GCP) and infrastructure as code (e.g., Terraform, Ansible)

Preferred Qualifications

• Hands-on experience with AIOps platforms or building ML-based incident response systems
• Background in log analysis, time-series forecasting, or unsupervised anomaly detection
• Knowledge of Kubernetes, container orchestration, and service mesh architectures
• Exposure to ITSM/ITIL processes and how they integrate with AIOps
• Ability to communicate ML results to operational teams and implement iterative improvements