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Ernst & Young

Global professional services: consulting, assurance, tax

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

Applied Machine LearningUpdated on Nov 14
Full-timeNoida, Uttar Pradesh, IndiaNo salary listedIn-person

About the Job

Requirements

  • At least 9 years of experience in IT operations, DevOps, or Site Reliability Engineering, including 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 such as Moogsoft, BigPanda, Splunk ITSI, ServiceNow ITOM, or custom machine-learning-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.
  • Experience with CI/CD tools such as Azure DevOps, GitHub Actions, and Jenkins; infrastructure-as-code tools such as Terraform and Ansible; and Kubernetes.
  • Familiarity with observability stacks such as ELK, OpenTelemetry, and Kafka, and with data engineering workflows.
  • A B.Tech. or Bachelor of Science degree in Computer Science.
  • Certification in a cloud platform, such as Azure Data Engineer Associate, AWS Data Analytics, or Google Data Engineer.
  • Proficiency in Python, SQL, and Bash for automation and data workflows.
  • Experience with Apache Kafka, Spark, AWS Glue, and ETL tools such as NiFi, Talend, or ADF.
  • Skill in managing data on Azure Data Lake, Amazon Redshift, or BigQuery.
  • Familiarity with CI/CD, Terraform, Docker, Kubernetes, and monitoring tools such as Prometheus and Grafana.
  • Strong understanding of DevSecOps, data governance, and compliance frameworks.
  • Understanding of monitoring tools such as Prometheus, Grafana, and ELK, and DevSecOps principles.

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 Prometheus, Grafana, AppDynamics, Dynatrace, and Azure Monitor into centralized AIOps platforms for unified observability and intelligent event correlation.
  • Design and maintain machine-learning 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, Site Reliability Engineering, 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 machine-learning-based filtering, deduplication, and suppression techniques to improve the 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.

About the Company

Ernst & Young

Global professional services: consulting, assurance, tax

EY (Ernst & Young) provides professional services at a global scale, offering consulting, assurance, tax, and transaction advisory services. It serves clients across industries such as technology, media, real estate, hospitality, and construction. Instead of selling a single product, EY works with clients through tailored engagements where cross-disciplinary teams analyze challenges, design strategies, perform audits, help with tax planning, and assist with mergers or divestitures. What sets EY apart is its worldwide reach and integrated service model, industry-specific expertise, and focus on responsible business practices like sustainability, cybersecurity, and workforce flexibility. EY’s goal is to help organizations improve performance, manage risk, and achieve sustainable growth while building a better working world.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Boston, MA
Founded
1991

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