Lead Application Production Support

Key Responsibilities

1. Production Support Leadership

• Lead L1/L2/L3 support teams ensuring high availability and SLA adherence.
• Own incident, problem, and escalation management across applications.

• Implement frameworks to reduce manual intervention.

• Manage MIS etc to monitor data of production support 

• Coordinate with Application teams for Permanent fixes

• Manage production change control to avoid service disruption

• Drive faster resolution of critical production issues.

• Collaborate with release managers for seamless deployments
• Oversee incident lifecycle with AI-assisted triaging and prioritization.
• Ensure detailed RCA with data-driven insights.
• Reduce recurring incidents using predictive models.

• Implement AI/ML-based monitoring and predictive analytics to identify potential failures.
• Leverage AIOps tools for anomaly detection and intelligent alerting.
• Drive auto-remediation and self-healing systems.
• Use AI for log analysis, pattern recognition, and root cause prediction.

3. Incident & Problem Management

4. Stakeholder & Business Engagement

• Act as a bridge between business, IT, and data teams.
• Translate AI-driven insights into actionable business improvements.
• Manage vendors and partners effectively.

5. Change & Release Governance

• Monitor post-deployment health using intelligent dashboards.

7. Automation & Innovation

• Drive automation using AI, RPA, and scripting.
• Build intelligent workflows to reduce manual intervention.
• Continuously improve operational efficiency using data insights.

8. Team Management & Capability Building

• Mentor team on AI tools, automation, and modern support practices.
• Upskill team in data-driven decision-making and AI adoption.

Required Skills & Qualifications

• Bachelor’s degree in Computer Science / IT or related field.
• 8–10 years of experience in application/product support from GI industry
• Strong experience in incident, problem, and change management.
• Hands-on experience with tools like ServiceNow, JIRA.
• Good understanding of databases, APIs, and integrations.
• Exposure to cloud platforms such as Amazon Web Services and Microsoft Azure.
• Must have AI & Technical Capabilities
• Understanding of AI/ML concepts (supervised/unsupervised learning, anomaly detection).
• Experience with AIOps platforms (e.g., Dynatrace, Moogsoft, Splunk).

• Expertise in insurance platforms (like GC ), policy issuance systems, claims workflows, reinsurance & accounting.

• Knowledge of cloud platforms (AWS, Azure) and CI/CD tools (Jenkins, Ansible etc).

Ability to use AI for:

• Log analysis and incident prediction
• Automated ticket classification and routing
• Chatbots / virtual assistants for L1 support
• Basic scripting / programming (Python preferred for AI use cases).
• Familiarity with data analysis and visualization tools.
• Exposure to GenAI use cases (knowledge assistants, automated RCA summaries).

Preferred Skills

• ITIL certification
• BFSI / General Insurance domain experience
• Experience in large-scale digital platforms
• Exposure to RPA tools and workflow automation

Key Responsibilities

1. Production Support Leadership

• Lead L1/L2/L3 support teams ensuring high availability and SLA adherence.
• Own incident, problem, and escalation management across applications.

• Implement frameworks to reduce manual intervention.

• Manage MIS etc to monitor data of production support 

• Coordinate with Application teams for Permanent fixes

• Manage production change control to avoid service disruption

• Drive faster resolution of critical production issues.

• Collaborate with release managers for seamless deployments
• Oversee incident lifecycle with AI-assisted triaging and prioritization.
• Ensure detailed RCA with data-driven insights.
• Reduce recurring incidents using predictive models.

• Implement AI/ML-based monitoring and predictive analytics to identify potential failures.
• Leverage AIOps tools for anomaly detection and intelligent alerting.
• Drive auto-remediation and self-healing systems.
• Use AI for log analysis, pattern recognition, and root cause prediction.

3. Incident & Problem Management

4. Stakeholder & Business Engagement

• Act as a bridge between business, IT, and data teams.
• Translate AI-driven insights into actionable business improvements.
• Manage vendors and partners effectively.

5. Change & Release Governance

• Monitor post-deployment health using intelligent dashboards.

7. Automation & Innovation

• Drive automation using AI, RPA, and scripting.
• Build intelligent workflows to reduce manual intervention.
• Continuously improve operational efficiency using data insights.

8. Team Management & Capability Building

• Mentor team on AI tools, automation, and modern support practices.
• Upskill team in data-driven decision-making and AI adoption.

Required Skills & Qualifications

• Bachelor’s degree in Computer Science / IT or related field.
• 8–10 years of experience in application/product support from GI industry
• Strong experience in incident, problem, and change management.
• Hands-on experience with tools like ServiceNow, JIRA.
• Good understanding of databases, APIs, and integrations.
• Exposure to cloud platforms such as Amazon Web Services and Microsoft Azure.
• Must have AI & Technical Capabilities
• Understanding of AI/ML concepts (supervised/unsupervised learning, anomaly detection).
• Experience with AIOps platforms (e.g., Dynatrace, Moogsoft, Splunk).

• Expertise in insurance platforms (like GC ), policy issuance systems, claims workflows, reinsurance & accounting.

• Knowledge of cloud platforms (AWS, Azure) and CI/CD tools (Jenkins, Ansible etc).

Ability to use AI for:

• Log analysis and incident prediction
• Automated ticket classification and routing
• Chatbots / virtual assistants for L1 support
• Basic scripting / programming (Python preferred for AI use cases).
• Familiarity with data analysis and visualization tools.
• Exposure to GenAI use cases (knowledge assistants, automated RCA summaries).

Preferred Skills

• ITIL certification
• BFSI / General Insurance domain experience
• Experience in large-scale digital platforms
• Exposure to RPA tools and workflow automation

• Bachelor’s degree in Computer Science / IT or related field.
• 8–10 years of experience in application/product support from GI industry
• Strong experience in incident, problem, and change management.
• Hands-on experience with tools like ServiceNow, JIRA.
• Good understanding of databases, APIs, and integrations.
• Exposure to cloud platforms such as Amazon Web Services and Microsoft Azure.
• Must have AI & Technical Capabilities
• Understanding of AI/ML concepts (supervised/unsupervised learning, anomaly detection).
• Experience with AIOps platforms (e.g., Dynatrace, Moogsoft, Splunk).

• Expertise in insurance platforms (like GC ), policy issuance systems, claims workflows, reinsurance & accounting.

• Knowledge of cloud platforms (AWS, Azure) and CI/CD tools (Jenkins, Ansible etc).