CloudOps AIOPs Engineer

Overview

On Site
Contract - W2
Contract - Independent
Contract - 12 Month(s)

Skills

Computer Science
Science
Research
SANS
Artificial Intelligence
FOCUS
Reliability Engineering
Management
Root Cause Analysis
Predictive Analytics
Collaboration
Continuous Integration
Continuous Delivery
Orchestration
Continuous Improvement
Dynatrace
Splunk
New Relic
Scripting
Python
Bash
Windows PowerShell
Amazon Web Services
Microsoft Azure
Google Cloud
Google Cloud Platform
DevOps
IDP
GitHub
Analytical Skill
Problem Solving
Conflict Resolution
Machine Learning (ML)
Analytics
IT Service Management
ServiceNow
Incident Management
Workflow
Cloud Computing

Job Details

Title CloudOps AIOPs Engineer

Location New York ( Hybrid 2-3 days onsite)

Duration: 12 months contract

Skill List

AIOps, artificial intelligence, computer science, science & research

Role Overview:

We are looking for a proactive and analytical AIOps Engineer to design, implement, and optimize AI-driven operational intelligence solutions. This role will focus on leveraging machine learning, event correlation, and automation to enhance observability, reduce incident noise, and improve system reliability across cloud and hybrid environments.

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Key Responsibilities:

Implement and manage AIOps platforms to enable intelligent alerting, anomaly detection, and root cause analysis.

Integrate AIOps capabilities with observability tools (e.g., New Relic) and incident management systems (e.g., PagerDuty).

Develop event correlation rules, noise reduction strategies, and predictive analytics to support proactive operations.

Collaborate with SRE, Cloud, and Application teams to embed AIOps into CI/CD and production workflows.

Automate operational tasks and remediation workflows using scripting and orchestration tools.

Monitor and fine-tune AIOps models to ensure accuracy, relevance, and performance.

Contribute to the observability and RunOps strategy, driving continuous improvement through data-driven insights.

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Required Skills & Experience:

Experience with AIOps platforms (e.g., Moogsoft, BigPanda, Dynatrace, Splunk ITSI, or similar).

Strong understanding of observability concepts (metrics, logs, traces) and tools like New Relic, Datadog, or Prometheus.

Proficiency in scripting and automation (Python, Bash, PowerShell).

Experience with cloud platforms like AWS (preferred), Azure, or Google Cloud Platform and DevOps/SRE practices.

Experience with event correlation, anomaly detection, and ML-based alerting.

Working knowledge of IDP platforms and developer enablement tools.

Practical experience using GitHub Copilot for automation and code generation.

Strong analytical and problem-solving skills.

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Preferred Qualifications:

Exposure to machine learning models for operational analytics.

Experience with ITSM tools (e.g., ServiceNow) and incident response workflows.

Certifications in cloud platforms or AIOps tools.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.