Role Overview :

The AI Operations Production Support Specialist, 2 is responsible for ensuring the stability, performance, and availability of production systems through the application of Artificial Intelligence for IT Operations (AIOps) tools and methodologies. This role involves managing and optimizing AIOps platforms to proactively detect, diagnose, and resolve operational issues before they impact the business.

Essential Job Functions :

- Provide L1, L2, and L3 support for AIOps products.

- Monitor and support production operations, addressing client queries and ensuring smooth functionality, execution, and troubleshooting.

- Analyze and interpret operational data effectively.

- Develop and maintain Python scripts for automation and support activities.

- Independently understand and address client requirements and queries.

- Perform detailed data analysis to support decision-making processes.

- Collaborate with cross-functional teams to implement models and monitor outcomes.

- Provide regular updates to stakeholders on deployment status, risks, and issues.

- Stay up to date with the latest technology trends in AIOps, Artificial Intelligence, and related technologies.

- Continuously improve models and techniques to adapt to new data patterns and trends.

Minimum Qualifications :

- Bachelor's Degree in Computer Science, Engineering, or a related field of study.

- 2+ years of experience as a Production Support Analyst in AI Operations, Machine Learning Engineering, Data Science, Data Engineering, DevOps, Analytics, or related fields.

- Experience in retail financial services or information technology fields.

- Experience working with Agile methodologies.

Preferred Qualifications :

- 5+ years of experience in AI Operations, Machine Learning Engineering, Data Science, Data Engineering, DevOps, Analytics, or related fields.

Tech Stack :

- DevOps practices and production support processes.

- ServiceNow platform for incident, problem, and service management.

- Azure DevOps for development, deployment, monitoring, and operational activities.

- GitHub for source code management and collaboration.

- Machine Learning concepts, models, and implementation processes.

- Microsoft Excel for data analysis and reporting.

- JIRA for issue tracking and project management.

- Python for scripting, automation, and data analysis.