Tech S and T-AI Ops Engineer-Senior-GDSN02

EY; Thiruvananthapuram; On-site; INR 2,400,000 - 4,200,000; Full time

Job summary

EY is seeking a results-driven AIOps Manager to architect and implement enterprise-grade AIOps solutions across cloud and hybrid environments. You will lead data integration from telemetry tools and design ML models for anomaly detection, while building scalable data pipelines and self-healing automation.

You will collaborate with DevOps, SRE, and platform engineering teams to embed AIOps into CI/CD workflows, develop dashboards, and optimize alerting using ML-based noise reduction.

Qualifications

• 9+ years of experience in IT operations, DevOps, or SRE, with at least 3 years in AIOps or AI/ML-driven automation.
• Proven experience in technical leadership, team management, and cross-functional collaboration.
• Deep expertise in AIOps platforms: Moogsoft, BigPanda, Splunk ITSI, ServiceNow ITOM, or custom ML-based solutions.

Responsibilities

• Architect and implement enterprise-grade AIOps solutions to automate incident detection, root cause analysis, and remediation across cloud and hybrid environments.
• Lead the integration of telemetry data from tools like Prometheus, Grafana, AppDynamics, Dynatrace, and Azure Monitor into centralized AIOps platforms for unified observability and intelligent event correlation.
• Design and maintain ML models in Python for anomaly detection, predictive analytics, and operational forecasting, ensuring scalability and accuracy.
• Build and optimize real-time and batch data pipelines using Apache Kafka, Logstash, and Fluentd to process logs, metrics, and traces from distributed systems.
• Collaborate with DevOps, SRE, and platform engineering teams to embed AIOps capabilities into CI/CD workflows and infrastructure-as-code practices.
• Drive automation of operational tasks and remediation workflows using Python, Azure Functions, and orchestration tools to enable self-healing systems.
• Develop dashboards and visualizations using Grafana, Kibana, or Power BI to deliver actionable insights to engineering, operations, and business teams.
• Implement alert noise reduction strategies using ML-based filtering, deduplication, and suppression techniques to improve signal-to-noise ratio.
• Ensure compliance with security, governance, and audit policies, embedding DevSecOps principles and aligning with regulatory standards.
• Lead technical evaluations of AIOps platforms and tools, making recommendations for adoption based on business needs and operational maturity.
• Manage and mentor a team of AIOps engineers, fostering a culture of innovation, continuous learning, and operational excellence.
• Partner with business stakeholders to identify opportunities for cost optimization, risk reduction, and service reliability improvements through AIOps.
• Contribute to strategic roadmaps, budget planning, and vendor assessments, aligning AIOps initiatives with broader IT and business goals.
• Stay current with emerging trends in AIOps, observability, cloud-native operations, and AI-driven automation, and drive their adoption within the organization.

Skills

AIOps leadership

Technical leadership

Team management

Python

Cloud platforms (Azure, AWS, GCP)

Tools

Moogsoft

BigPanda

Splunk ITSI

ServiceNow ITOM

Kubernetes

Terraform

Ansible

Jenkins

Azure DevOps

GitHub Actions

Job description

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.Designation AIOps ManagerJob Description

• Architect and implement enterprise-grade AIOps solutions to automate incident detection, root cause analysis, and remediation across cloud and hybrid environments.
• Lead the integration of telemetry data from tools like Prometheus, Grafana, AppDynamics, Dynatrace, and Azure Monitor into centralized AIOps platforms for unified observability and intelligent event correlation.
• Design and maintain ML models in Python for anomaly detection, predictive analytics, and operational forecasting, ensuring scalability and accuracy.
• Build and optimize real-time and batch data pipelines using Apache Kafka, Logstash, and Fluentd to process logs, metrics, and traces from distributed systems.
• Collaborate with DevOps, SRE, and platform engineering teams to embed AIOps capabilities into CI/CD workflows and infrastructure-as-code practices.
• Drive automation of operational tasks and remediation workflows using Python, Azure Functions, and orchestration tools to enable self-healing systems.
• Develop dashboards and visualizations using Grafana, Kibana, or Power BI to deliver actionable insights to engineering, operations, and business teams.
• Implement alert noise reduction strategies using ML-based filtering, deduplication, and suppression techniques to improve signal-to-noise ratio.
• Ensure compliance with security, governance, and audit policies, embedding DevSecOps principles and aligning with regulatory standards.
• Lead technical evaluations of AIOps platforms and tools, making recommendations for adoption based on business needs and operational maturity.
• Manage and mentor a team of AIOps engineers, fostering a culture of innovation, continuous learning, and operational excellence.
• Partner with business stakeholders to identify opportunities for cost optimization, risk reduction, and service reliability improvements through AIOps.
• Contribute to strategic roadmaps, budget planning, and vendor assessments, aligning AIOps initiatives with broader IT and business goals.
• Stay current with emerging trends in AIOps, observability, cloud-native operations, and AI-driven automation, and drive their adoption within the organization.

Desired Profile

• 9+ years of experience in IT operations, DevOps, or SRE, with at least 3 years in AIOps or AI/ML-driven automation.
• Proven experience in technical leadership, team management, and cross-functional collaboration.
• Deep expertise in AIOps platforms: Moogsoft, BigPanda, Splunk ITSI, ServiceNow ITOM, or custom ML-based solutions.
• Strong proficiency in Python, with working knowledge of SQL, PowerShell, and Bash.
• Hands-on experience with Azure, AWS, or GCP, including monitoring and automation services.
• Skilled in CI/CD tools (Azure DevOps, GitHub Actions, Jenkins), IaC (Terraform, Ansible), and Kubernetes.
• Familiarity with observability stacks (ELK, OpenTelemetry, Kafka) and data engineering workflows.
• Excellent communication, stakeholder management, and problem-solving skills.

Experience: 9 years and above