AI/ML Senior Project Manager

About The Singapore AI Center Of Excellence (COE)

The Singapore AI Center of Excellence (COE) is a dedicated engineering and R&D hub focused on Enterprise and Sovereign AI. Our mission is to help organizations move AI workflows cleanly into production through two main paths: creating reusable software architectures that solve common industry problems, and contributing code directly to upstream open-source projects to fix enterprise gaps in system deployment, runtime tuning, and platform management.

Basing our engineering team in Singapore creates a close feedback loop between customers, partners, and core product teams. This direct connection keeps our development roadmaps relevant, speeds up solution delivery, and strengthens our ability to co-innovate across the region.

About The Job

The AI/ML Senior Project Manager is a pivotal, delivery-focused leadership role responsible for directing and orchestrating the execution of AI/ML solution blueprints and open-source AI Quickstarts within the Customer Engineering team. Managing the delivery lifecycle of our AI/ML Architects and AI/ML Engineers, you will translate highly ambiguous enterprise problems into pragmatic, high-velocity roadmaps (targeting 1-to-3 month execution cycles).

Operating at the intersection of business strategy and technical execution, your mission is to maintain delivery velocity, remove organizational and technical blockers, and ensure that our technical blueprints are structured for seamless handover to downstream implementation and services teams.

What You Will Do

Technical Squad Orchestration: Direct and manage the day-to-day delivery of AI/ML Engineers and Architects. Coordinate matrixed resources to ensure project milestones are achieved efficiently, on time, and aligned with engineering standards.
Agile Scope & Delivery Governance: Establish and enforce lean, agile delivery frameworks (such as Scrum or Kanban) to accelerate time-to-first-value. Act as a facilitator to set shared milestones, track team velocity, and run continuous delivery cycles.
Workshop Facilitation & Scoping: Lead discovery workshops and scoping sessions with enterprise clients. Guide business and technical stakeholders to clarify high-priority problems worth solving, distinguish viable AI use cases, and define clear Minimum Viable Product (MVP) boundaries.
Blocker Removal & Risk Mitigation: Proactively identify, track, and resolve program-level risks, interdependencies, and technical bottlenecks. Coordinate directly with partners, customer teams, and product hubs to unblock implementation paths.
Roadmap & Output Packaging: Partner with architects and engineers to package completed architectures into repeatable, extensible, and open-sourced AI Quickstarts. Ensure all deliverables include the high-quality documentation, architectural blueprints, and validation matrices required for long-term customer success.
Performance & Impact Reporting: Coordinate the collection of operational metrics, EDB reporting benchmarks, and team utilization data. Communicate clear status updates, project milestones, and value metrics to senior regional and global leadership.

What You Will Bring

Academic & Professional Experience

Education: Bachelor’s degree in Computer Science, Engineering, Information Technology, Business Management, or a related field.
Consulting & Engagement Leadership: Proven track record of leading consulting engagements, agile delivery, or enterprise-level digital transformations for technical stakeholders.
Structured Delivery DNA: Exceptional organizational and task-management skills, with a deep understanding of lean software development, DevOps cultures, and product-led ways of working.

Project & Agile Methodology

Agile Framework Mastery: Experience teaching, implementing, and optimizing agile methodologies (e.g., Scrum, Kanban, SAFe) in complex software development environments.
Tooling Proficiency: Strong hands-on experience using industry-standard project, portfolio, and backlog management tools.
Stakeholder Management: Exceptional communication and facilitation skills, with a demonstrated ability to negotiate project constraints, manage expectations, and build trust with diverse stakeholder groups across APAC.

Target Knowledge Domains & Growth Areas

Skills

We are building a multi-disciplinary delivery and project coordination squad. Candidates are expected to bring experience in some of the following domains, and will have the opportunity to continuously develop their skills across all of them as they grow in seniority:

Practical AI/ML Literacy: Strong conceptual understanding of current machine learning lifecycles (data preparation, model fine-tuning, and model serving runtimes) and common application patterns (e.g., Retrieval-Augmented Generation, autonomous agents, and workflow automation).
Cloud-Native & Platform Delivery Foundations: Familiarity with the operational principles of modern container infrastructure, enterprise Kubernetes platforms, and platform engineering team structures (e.g., stream-aligned vs. enabling teams).
Enterprise Compliance, Governance, & Security: Understanding of the operational constraints, change management, and responsible AI guardrails (such as data privacy, system vulnerability checking, and risk compliance) required to successfully deploy technical platforms inside regulated networks.
Incremental ROI & Value Mapping: Proficiency in mapping project outputs directly to customer value realization metrics, using tools such as value stream mapping and incremental delivery scoring.

Nice-to-Have: Industry Domain Experience

Required

While not strictly required, experience managing technology delivery, compliance frameworks, or digital transformations in the following highly regulated sectors is a strong advantage:

Financial Services (FSI): Experience working under strict regulatory compliance, risk management frameworks, or financial operational guidelines.
Public Sector & Healthcare: Ex