We're looking for a forward-thinking Intelligent Automation Engineer to join our growing engineering team. In this role, you'll build and scale automation solutions that drive system resilience, reduce incident resolution time, and enable intelligent, self-healing infrastructure. You'll be at the heart of our automation strategy--embedding knowledge into bots, predicting failures before they happen, and eliminating repetitive tasks across our tech stack.This is an opportunity to shape the future of operational excellence at a fast-moving tech company where innovation, speed, and quality matter. What You'll Do: Build intelligent bots and dynamic scripts that automate knowledge and action across key systems and services. Accelerate incident resolution through data-driven diagnostics and automated recovery flows. Implement predictive anomaly detection and self-healing mechanisms to prevent outages and reduce manual intervention. Automate repetitive fixes and workarounds, freeing up engineering time and reducing alert fatigue. Enhance alert correlation and early incident detection by applying AI/ML models to observability and telemetry data. Consolidate automation efforts across teams, ensuring visibility, accountability, and tracking of progress to avoid duplication. Collaborate with SREs, DevOps, and software engineers to integrate automation into CI/CD pipelines, monitoring systems, and production environments. Use incident and performance data to continuously identify areas for improvement and automation expansion.
Requirements:
3-7 years of hands-on experience in automation engineering, DevOps, or infrastructure roles. Proficiency in scripting and programming (Python preferred) and infrastructure automation (Terraform, Ansible, etc.). Experience with observability platforms (e.g., Datadog, Splunk, Prometheus, Grafana) and incident management workflows. Understanding of anomaly detection, predictive analytics, and AIOps practices. Strong collaboration and communication skills--you'll be working across multiple teams and systems.Nice-to-Haves: Experience with chatbot or conversational AI frameworks (e.g., Microsoft Bot Framework, Dialogflow). Familiarity with cloud-native ecosystems (AWS, GCP, or Azure) and Kubernetes-based environments. Exposure to ITSM tools and process frameworks (e.g., ServiceNow, ITIL).
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