AI Observability Engineer

ncr; Atlanta (GA); On-site; USD 110,000 - 170,000; Full time

Job summary

NCR Voyix Corporation in Atlanta seeks an Observability Automation Engineer to design, implement, and support enterprise observability platforms while driving automation and AI initiatives.

You will build dashboards, automate incidents, and collaborate with SRE and cloud teams to improve reliability and scalability, leveraging tools like Splunk, AppDynamics, and OpenTelemetry.

This role emphasizes AI-assisted runbooks, self-healing workflows, and proactive monitoring to reduce MTTR.

Qualifications

• Bachelor's degree in CS/Engineering/IT or related field.
• 3+ years in Observability, SRE, Infrastructure or Ops engineering.
• Proficient in scripting: Python, PowerShell, Bash or similar.
• Experience with cloud platforms such as Azure, AWS, or GCP.

Responsibilities

• Design, deploy, and maintain enterprise observability platforms for monitoring, logging, tracing, and alerting.
• Develop dashboards, KPIs, and service health metrics for actionable insights.
• Automate incident management workflows, health checks, and runbooks.
• Collaborate with engineering/operations to improve performance and reliability.
• Advance AI-powered observability with anomaly detection and predictive analytics.

Skills

Observability

SRE

Automation

Cloud platforms

OpenTelemetry

AI tooling

Kubernetes

Education

Bachelor's degree in Computer Science/Engineering/IT

Tools

Splunk

AppDynamics

Splunk Observability Cloud

Terraform

Bicep

ARM

Kubernetes

LangChain

Semantic Kernel

Job description

About NCR VOYIX

NCR Voyix Corporation (NYSE: VYX) is a global platform-powered leader in unified commerce for shopping and dining. Combining a flexible, intelligent platform with end-to-end payments capabilities and services developed through its deep industry experience, NCR Voyix empowers retailers and restaurants to accelerate new possibilities for their operations, experiences and business outcomes. NCR Voyix is headquartered in Atlanta, Georgia, and serves customers in more than 35 countries worldwide.

Observability Automation Engineer

Role Summary

We are seeking an Observability Engineer to design, implement, and support enterprise observability platforms while driving automation, AI, and Agentic AI initiatives. The ideal candidate will leverage intelligent automation, AI-powered analytics, and autonomous agents to improve service reliability, accelerate troubleshooting, and reduce operational overhead.

Key Responsibilities

• Design, deploy, and maintain enterprise observability platforms for monitoring, logging, tracing, and alerting.
• Develop dashboards, KPIs, and service health metrics to provide actionable operational insights.
• Implement and optimize observability solutions using tools such as Splunk, AppDynamics, or Splunk Observability Cloud platforms.
• Automate operational processes, alert management, health checks, and incident response workflows using scripting and orchestration tools.
• Collaborate with engineering and operations teams to improve application performance, reliability, and scalability.
• Analyze incidents, identify root causes, and implement preventive measures through proactive monitoring and automation.
• Drive adoption of AI-powered observability capabilities, including anomaly detection, predictive analytics, event correlation, and intelligent alerting.
• Leverage Microsoft Copilot, Generative AI, and automation technologies to enhance troubleshooting, operational efficiency, and engineering productivity.
• Develop AI-assisted runbooks, knowledge bases, and self-healing solutions to reduce manual intervention and Mean Time to Resolution (MTTR).
• Participate in on-call support and major incident management activities as needed.
• Design and implement AI-driven observability solutions using telemetry, monitoring, logging, and distributed tracing platforms.
• Develop automated remediation, self-healing workflows, and operational runbooks using scripting, orchestration, and infrastructure-as-code tools.
• Build and integrate Agentic AI solutions that can autonomously analyze alerts, retrieve operational context, recommend actions, and execute approved remediation workflows.
• Leverage Microsoft Copilot and Generative AI tools to improve incident investigation, root-cause analysis, knowledge management, and engineering productivity.
• Implement AI-powered anomaly detection, event correlation, capacity forecasting, and predictive monitoring capabilities.
• Develop integrations between observability platforms and AI agents to automate repetitive operational tasks and improve MTTR.
• Collaborate with application, SRE, cloud, and platform teams to identify opportunities for AI-assisted operations and process automation.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Technology, or related field.
• 3+ years of experience in Observability, Site Reliability Engineering (SRE), Infrastructure Engineering, or Operations Engineering.
• Strong experience with monitoring, logging, tracing, and performance management platforms.
• Proficiency in scripting and automation using Python, PowerShell, Bash, or similar languages.
• Experience working with cloud platforms such as Microsoft Azure, AWS, or Google Cloud.
• Knowledge of CI/CD pipelines, Infrastructure as Code (Terraform, Bicep, ARM, etc.), and DevOps practices.
• Experience with Python, PowerShell, or similar languages for automation and API integrations.
• Experience developing automation workflows and integrating observability platforms with cloud services and operational tools.
• Familiarity with AI-assisted engineering practices and Copilot-enabled development workflows.
• Strong analytical and troubleshooting skills.

Preferred Qualifications

• Experience with Microsoft Copilot, Azure OpenAI, Copilot Studio, or other AI-powered engineering tools.
• Knowledge of AIOps platforms and machine learning concepts related to observability.
• Experience implementing OpenTelemetry standards and distributed tracing solutions.
• Familiarity with Kubernetes, containers, and cloud-native monitoring architectures.
• Experience building automated remediation and self-healing workflows.
• Hands-on experience with Microsoft Copilot, Azure AI Services, Azure OpenAI, Copilot Studio, LangChain, Semantic Kernel, Agentic AI frameworks, or similar technologies.
• Experience building AI agents, retrieval-based knowledge systems, AI-powered chatbots, or autonomous operational workflows.
• Knowledge of RAG architectures, vector databases, prompt