Job Description

Your Role

• 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)
• Monitor model performance, manage retraining cycles, and ensure AI reliability

Your Profile

• 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, Splunk, OpenTelemetry)
• Experience with public cloud platforms (AWS, Azure, GCP) and infrastructure as code (e.g., Terraform, Ansible)
• 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"a

What will you love working at Capgemini

• Work with modern technologies across enterprise‑grade digital solutions.
• Grow your technical expertise through continuous learning and structured career paths.
• Collaborate in high‑performing engineering teams delivering solutions at scale.
• Benefit from a flexible, professional work environment that supports productivity and innovation.