New opportunity

Deputy Manager - Application Support & Automation

ST Logistics Pte Ltd · Singapore

About this role

The Deputy Manager - Application Support & Automation owns the end-to-end support model for the organization's business applications. This role balances reliable business-as-usual (BAU) support with a strategic shift-left transformation by delivering an AI-powered L1 support agent. Responsibilities include managing the support function, serving as the L2 escalation authority, and codifying resolutions into knowledge catalogues to expand the agent's autonomous coverage. Key tasks include defining the AI support roadmap, governing knowledge frameworks, monitoring agent performance metrics, and managing vendor relationships. Candidates must hold a degree in IT or Computer Science and possess 6-10 years of experience in application support or ITSM, with at least 2 years in a lead or managerial capacity. Proven experience in delivering support automation, chatbots, or virtual agents (e.g., ServiceNow Virtual Agent, Microsoft Copilot Studio, or LLM-based solutions) is required. Strong hands-on experience with ITSM platforms and ITIL-aligned processes is essential. ITIL Foundation certification is mandatory, while ITIL Managing Professional or equivalent is preferred.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Application SupportIT Service ManagementAutomationAI AgentsChatbotsVirtual AgentsServiceNow Virtual AgentMicrosoft Copilot StudioLLMITSMJira Service ManagementFreshserviceITILKnowledge ManagementIncident ManagementProblem ManagementChange ManagementVAPT

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Shift-Left AI Transformation
The primary strategic objective is to transition from manual L1 support to an AI-powered autonomous model. You must define the roadmap, govern the knowledge framework, and ensure the AI agent effectively resolves common issues to reduce human workload.
ITSM and BAU Service Delivery
Maintaining stable business-as-usual operations is critical. This requires rigorous adherence to ITIL-aligned incident, problem, and change management processes while serving as the L2 escalation authority for complex application issues.
Knowledge Management Governance
Success depends on codifying L2 resolutions into structured knowledge assets. You must establish a feedback loop that converts manual troubleshooting into AI-ready content, directly impacting the agent's deflection rate and autonomous coverage.

Likely challenges to think through

Balancing Automation with Service Stability
A common challenge is maintaining high service levels during the transition to AI. Prepare to discuss how you manage the risk of AI misconfigurations or knowledge gaps that could lead to increased L2 escalations or user dissatisfaction during the implementation phase.
Stakeholder Adoption of Self-Service
Driving cultural change is difficult when users are accustomed to human support. Prepare to explain your strategy for user engagement, training, and communication to ensure business stakeholders trust and utilize the new AI-powered self-service capabilities.

Practice your answers

Technical practice

Designing an AI-Powered L1 Support Roadmap

What to coverExplain how you would define the scope for an AI-powered support agent. Focus on identifying high-volume, low-complexity incidents suitable for automation and how you would prioritize these based on business impact and feasibility.

Knowledge Management for Automation

What to coverDescribe your process for converting L2 manual resolutions into structured knowledge assets. Discuss how you ensure these articles are machine-readable and effective for training LLM-based or virtual agent solutions.

Measuring Shift-Left Success

What to coverWhich specific KPIs would you track to evaluate the effectiveness of an AI support agent? Address metrics like deflection rate, first-contact resolution, and how you correlate these with a reduction in manual L2 escalations.

ITIL Incident and Problem Management Integration

What to coverHow do you ensure that automated L1 support remains compliant with ITIL processes? Discuss the balance between rapid automated resolution and the need for proper incident logging, categorization, and root cause analysis.

Managing VAPT Remediation

What to coverDescribe your approach to coordinating the remediation of Vulnerability Assessment and Penetration Testing (VAPT) findings. Focus on how you prioritize security patches alongside BAU application support and vendor management.

Vendor Management for AI Platforms

What to coverWhen managing third-party AI or ITSM platform vendors, what criteria do you use to evaluate service delivery and performance? Suggestion: Focus on SLA governance, roadmap alignment, and ensuring vendor support meets internal technical requirements.

Handling Complex L2 Escalations

What to coverAs the L2 escalation authority, how do you manage the handover process from an AI agent to a human agent? Explain how you ensure the human agent receives sufficient context to resolve the issue without repeating troubleshooting steps.

Platform Experience: ServiceNow or Copilot Studio

What to coverDiscuss your hands-on experience with platforms like ServiceNow Virtual Agent or Microsoft Copilot Studio. Highlight a specific challenge you faced in configuring these tools and how you optimized the agent's performance.

Behavioural practice

Driving Cultural Change in Support Teams

What to coverDescribe a time you introduced automation to a team that was accustomed to manual processes. How did you address resistance and encourage the team to adopt a 'shift-left' mindset?

Stakeholder Management and Prioritization

What to coverProvide an example of how you balanced competing demands from business stakeholders for new application features versus the need for stable BAU support. How did you communicate your prioritization decisions?

Leading Through Technical Challenges

What to coverTell me about a time you had to lead a team through a critical system incident. How did you coordinate the response, manage vendor communication, and ensure stakeholders were kept informed?

Continuous Improvement Initiative

What to coverGive an example of a process improvement you implemented that significantly reduced manual effort. What was the situation, what specific action did you take, and what was the measurable result?

Sharpen your knowledge

Topics to prepare

Shift-Left Transformation Strategy
Understand the conceptual framework of moving support from L2 human intervention to L1 AI-driven resolution. Exercise: Draft a high-level roadmap for transitioning a common recurring incident type from manual L2 resolution to an automated L1 knowledge-based workflow.
ITIL-Aligned Knowledge Management
Focus on the governance of knowledge assets within an ITSM environment. Exercise: Design a structured feedback loop that captures L2 resolution data and converts it into a standardized troubleshooting guide or decision tree for an AI agent.
AI Agent Performance Metrics
Study key performance indicators for virtual support agents. Exercise: Define how you would measure and report on 'deflection rate' and 'escalation quality' to stakeholders to demonstrate the ROI of an AI-powered support initiative.

Skills to revise

AI Agent Implementation
Practical application of virtual agent platforms. Exercise: Review the documentation for Microsoft Copilot Studio or ServiceNow Virtual Agent to understand how to configure intent-based responses and integrate them with existing knowledge base articles.
ITSM Platform Administration
Hands-on management of incident, problem, and change management workflows. Exercise: Simulate the lifecycle of a high-priority incident in an ITSM tool, ensuring proper documentation, escalation paths, and final closure according to ITIL best practices.
VAPT Remediation Coordination
Managing security-related application updates. Exercise: Create a checklist for coordinating a patch deployment cycle that addresses a VAPT finding, including UAT, stakeholder communication, and post-deployment verification.

Your preparation checklist

Prepare an AI-driven support project case study
Draft a structured walkthrough of a past project where you implemented a chatbot, virtual agent, or LLM-based solution. Focus on the specific tools used (e.g., ServiceNow Virtual Agent, Microsoft Copilot Studio), the metrics improved (e.g., deflection rate, resolution time), and how you managed the transition from manual L2 support to automated L1 resolution.
Map your experience to ITIL-aligned ITSM processes
Create a summary document detailing your hands-on experience with Incident, Problem, and Change Management. Explicitly link your past actions to ITIL frameworks, specifically highlighting how you have used these processes to drive continuous improvement and reduce recurring escalations.
Develop a knowledge management framework proposal
Outline a strategy for converting complex L2 manual resolutions into structured knowledge assets. Include your approach for maintaining decision trees, FAQs, and troubleshooting guides to ensure they remain effective for AI-powered L1 support agents.
Prepare for VAPT and vendor management discussions
Review your experience in coordinating VAPT (Vulnerability Assessment and Penetration Testing) remediation and managing third-party vendor relationships. Prepare concrete examples of how you have balanced vendor service delivery with internal security and performance requirements.
Formulate strategic questions for the interview
Prepare questions regarding the current maturity of their ITSM platform, the specific business applications currently in scope for automation, and the primary challenges stakeholders face with the existing support model to demonstrate your strategic thinking.

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