Dynatrace + AI Engineer

Job Description:

We are looking for a skilled Dynatrace + AI Engineer to enhance our observability and AIOps capabilities. This role involves implementing and optimizing Dynatrace solutions, leveraging AI-driven insights for proactive monitoring, incident management, and performance optimization. The ideal candidate will have expertise in Dynatrace, AI/ML, and cloud environments, ensuring high availability and performance of critical applications.

Key Responsibilities:

• Deploy, configure, and optimize Dynatrace for full-stack observability, including infrastructure, applications, and cloud environments.
• Implement AI-powered monitoring and anomaly detection to proactively identify and resolve performance bottlenecks.
• Utilize Dynatrace Davis AI for automated root cause analysis and predictive analytics.
• Integrate Dynatrace with AIOps platforms and automation tools to enhance incident response and remediation.
• Define and implement custom dashboards, alerts, and reports to provide actionable insights.
• Work closely with DevOps, SRE, and Cloud teams to optimize system performance and reliability.
• Conduct performance testing and tuning for applications using AI-driven analytics.
• Stay updated on emerging trends in AIOps, observability, and Dynatrace innovations.

Required Skills & Qualifications:

• 3+ years of experience with Dynatrace, including setup, configuration, and troubleshooting.
• Experience with Dynatrace Davis AI, Smartscape, and Business Analytics.
• Strong knowledge of AIOps, machine learning, and predictive analytics in observability.
• Familiarity with cloud platforms like AWS, Azure, or GCP and Kubernetes.
• Proficiency in automation scripting (Python, PowerShell, or Ansible) for monitoring tasks.
• Experience with CI/CD pipelines and DevOps practices.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.

Preferred Qualifications:

• Certification in Dynatrace, AI/ML, or Cloud (AWS/Azure/GCP).
• Experience with log analytics tools like Splunk, ELK, or Datadog.
• Hands-on experience in IT operations analytics (ITOA) and predictive maintenance.