New opportunity

Senior Program Manager, Architecture Review Board

NVIDIA · Singapore

About this role

The Senior Program Manager for the Architecture Review Board (ARB) will lead the APAC AI Factory ARB process, ensuring complex customer infrastructure designs are validated and deployment-ready. This role involves end-to-end management of architecture governance, deployment preparedness assessments, and cross-functional coordination across engineering, networking, storage, and security teams. Responsibilities include managing ARB schedules, decision logs, risk tracking, and executive reporting, while maintaining alignment with NVIDIA Reference Architectures and deployment standards. The manager will also drive improvements in ARB templates, automation, and AI-assisted workflow agents to scale governance across regions. Required Qualifications: Bachelor's degree in engineering, computer science, business, operations, or equivalent experience. Minimum 5 years of program or project management experience in large-scale infrastructure, cloud, networking, data center, hardware, or AI Factory deployment environments. Proven experience coordinating architecture reviews, governance boards, or technical approval processes. Strong understanding of AI infrastructure, GPU clusters, and technical validation processes. Proficiency in Jira for agile execution and risk management. Excellent communication skills for executive updates and translating technical risks into business impact. Preferred Qualifications: Experience with GPU-accelerated computing, HPC, DGX SuperPOD, and enterprise data center environments. Familiarity with NVIDIA Reference Architecture compliance and pre-deployment handoff processes. Experience with Salesforce and Wrike for pipeline tracking and reporting. Relevant certifications such as PMP, PgMP, Agile, or Scrum. Experience using AI tools like Copilot, Claude, Gemini, or Perplexity for program execution.

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

Skills for this role

Program ManagementProject ManagementArchitecture GovernanceAI InfrastructureGPU ClustersData Center OperationsJiraRisk ManagementDeployment Lifecycle ManagementStakeholder ManagementTechnical ValidationSalesforceWrikeAgileScrumPMPPgMP

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

End-to-End ARB Process Ownership
You must manage the entire lifecycle of the Architecture Review Board process for APAC AI Factory deployments. This requires balancing intake, technical validation, and pre-deployment handoff while ensuring all infrastructure designs align with strict NVIDIA Reference Architectures and deployment standards.
Cross-Functional Stakeholder Coordination
The role demands orchestrating diverse teams including engineering, networking, storage, security, and external OEM/Cloud partners. You must maintain clear communication channels, manage decision logs, and track blocking issues to ensure timely project progression.
Governance Scaling and Automation
Beyond daily management, you are expected to drive improvements in ARB templates, reporting, and workflow automation. This includes leveraging AI-assisted tools to scale governance processes across regions and partners effectively.
Executive Risk Reporting
You must translate complex technical risks and design exceptions into clear business impact updates for leadership. This requires high proficiency in documenting decision paths and maintaining transparency in risk tracking.

Likely challenges to think through

Balancing Rigorous Governance with Deployment Velocity
A core tension exists between maintaining strict adherence to NVIDIA Reference Architectures and meeting customer deployment timelines. Prepare by demonstrating how you have managed 'exception paths' in previous roles without compromising infrastructure integrity or project schedules.
Managing Diverse Technical Dependencies
Coordinating across specialized domains like GPU clusters, networking, and facilities involves high technical complexity. Prepare by highlighting your experience in identifying and resolving cross-functional bottlenecks in large-scale data center or AI infrastructure projects.
Adapting to Rapidly Evolving AI Infrastructure
The AI Factory environment is fast-paced and requires constant learning of new hardware and software standards. Prepare by discussing your experience with continuous improvement and how you utilize modern AI tools to streamline program execution and documentation.

Practice your answers

Technical practice

Managing Architecture Governance for AI Factories

What to coverExplain your approach to establishing and maintaining deployment gates for complex infrastructure. Focus on how you ensure alignment with Reference Architectures while managing exceptions for non-standard designs.

Technical Validation and Deployment Readiness

What to coverDescribe the key metrics and checkpoints you use to assess if a data center or GPU cluster design is ready for deployment. Discuss how you coordinate across networking, storage, and security teams to ensure a successful handoff.

Risk Management in Large-Scale Infrastructure

What to coverHow do you identify, track, and mitigate technical risks during the architecture review process? Suggestion: Highlight your experience using Jira to manage dependencies and blocking issues in high-stakes deployment environments.

Scaling Governance with Automation

What to coverDiscuss your experience in improving program workflows through automation or AI-assisted tools. Explain how you would use tools like Copilot or custom scripts to increase transparency and efficiency in an Architecture Review Board.

Translating Technical Risks for Executives

What to coverHow do you communicate complex infrastructure bottlenecks or design non-compliance to non-technical stakeholders? Focus on your method for quantifying business impact and securing executive buy-in for remediation paths.

Lifecycle Management of GPU Clusters

What to coverWhat are the unique challenges in managing the deployment lifecycle of AI-specific infrastructure like DGX SuperPODs compared to traditional enterprise data centers? Address the importance of hardware-software integration and power/cooling constraints.

Managing Cross-Functional Dependencies

What to coverDescribe your strategy for coordinating between internal engineering teams, OEM partners, and cloud providers. Explain how you maintain accountability when multiple parties are responsible for different segments of a single deployment.

Data-Driven Program Reporting

What to coverHow do you utilize tools like Salesforce or Wrike to maintain pipeline visibility and data quality? Suggestion: Explain how you build dashboards to track the health of the ARB process and identify regional trends.

Behavioural practice

Handling Conflicting Stakeholder Priorities

What to coverDescribe a situation where you had to balance the requirements of engineering teams against the constraints of a customer or partner. How did you facilitate a compromise that maintained architectural integrity?

Driving Process Improvement

What to coverGive an example of a time you identified a bottleneck in a governance or approval process and implemented a solution to fix it. What was the outcome, and how did you measure the success of the change?

Managing Through Ambiguity

What to coverTell me about a time you had to lead a program where the technical requirements were evolving rapidly. How did you maintain progress and keep the team aligned on the final deployment goal?

Accountability and Follow-Through

What to coverDescribe a time you had to hold a cross-functional team accountable for a critical blocking issue. How did you ensure the issue was resolved without damaging the working relationship?

Sharpen your knowledge

Topics to prepare

Architecture Governance Frameworks
Review the principles of establishing and maintaining technical design checkpoints and deployment gates. Exercise: Draft a hypothetical 'Architecture Review Board' charter that defines the intake, validation, and exception-handling process for a complex infrastructure project. This is relevant to your core responsibility of leading the APAC ARB process.
AI Infrastructure and GPU Clusters
Study the fundamental components of AI Factory deployments, including networking, storage, and GPU-accelerated computing. Exercise: Create a high-level checklist of technical dependencies required for a DGX SuperPOD deployment. This is relevant to your role in validating customer infrastructure designs against NVIDIA standards.
Technical Risk Management
Focus on identifying, tracking, and reporting on technical blockers in large-scale deployments. Exercise: Develop a template for an executive-level risk report that translates technical infrastructure issues into business impact. This is relevant to your requirement to provide clear updates to leadership.

Skills to revise

Jira for Program Governance
Practice using Jira for dependency tracking and lifecycle management. Exercise: Configure a Jira board workflow that tracks a project from initial intake through to deployment sign-off, including custom fields for risk status. This is relevant to the requirement for agile execution and risk management.
Workflow Automation and AI Tools
Explore using AI tools like Copilot or Gemini to automate documentation or reporting tasks. Exercise: Use an AI tool to summarize a complex technical design document into a concise executive summary. This is relevant to your goal of improving ARB templates and scaling governance through AI-assisted agents.
Pipeline Tracking in Salesforce and Wrike
Familiarize yourself with using CRM and project management tools for reporting. Exercise: Design a mock dashboard in a project management tool that tracks the status of multiple infrastructure reviews. This is relevant to the preferred qualification of using Salesforce and Wrike for pipeline transparency.

Your preparation checklist

Map your experience to AI infrastructure deployment
Prepare a summary of your past work in large-scale data center or cloud infrastructure projects. Specifically highlight your role in technical governance, managing deployment readiness, or coordinating cross-functional teams to validate complex hardware designs.
Develop a framework for technical risk reporting
Create a sample executive-level report template that translates technical infrastructure risks (e.g., networking bottlenecks, storage latency, or security gaps) into business impacts. This demonstrates your ability to communicate effectively with stakeholders.
Prepare a case study on process improvement
Draft a walkthrough of a time you improved a governance or approval process. Focus on how you used tools like Jira, Wrike, or AI-assisted agents to automate workflows, reduce bottlenecks, or improve transparency in a technical environment.
Review NVIDIA Reference Architecture concepts
Familiarize yourself with the general principles of NVIDIA's Reference Architectures and DGX SuperPOD deployments. Be prepared to discuss how you would manage compliance and exception handling when a customer design deviates from these standards.
Formulate strategic questions for the interview
Prepare thoughtful questions regarding the current scale of the APAC AI Factory ARB, the primary technical challenges in current deployment handoffs, and how the team balances speed of delivery with rigorous architectural governance.

Availability last checked: 18 Oct 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

KEEP EXPLORING

Similar AI jobs

Related skills and specializations in Singapore. Matched to this role, not your profile.

Explore more jobs

Finding similar opportunities…