AI ENABLEMENT LEAD

AI Enablement Lead

This is a newly created role at one of the most AI-forward companies in our sector. Reporting to the CTO with direct access to the CEO and C-Suite, the AI Enablement Lead will own the path from business problem through prioritization, requirements, technical delivery, adoption, and measurement. Working across business leadership, engineering, and IT, the role will turn AI opportunities into products, workflows, and capabilities while building the governance needed to scale across our US and Asia operations.

The mandate is to create measurable business value, using strong product management disciplines to move AI initiatives from definition through delivery and adoption.

The AI Enablement Lead will own three interconnected missions.

1. Turn C-Suite priorities into AI-enabled solutions

Embed with the CEO and C-Suite, attend key meetings, capture emerging initiatives, and frame the business problems and opportunities where AI can materially improve execution

Translate executive priorities into clear use cases and requirements, assess business value and technical feasibility with engineering and IT, and determine the right solution and delivery approach

Own priority initiatives from definition through delivery, managing scope, trade-offs, timelines, and stakeholder alignment while engineering and IT execute the technical work

Serve as a trusted thought partner to the leadership team on AI strategy, tooling, and emerging opportunity

1. Build the AI operating model and governance

Own and evolve Century's AI governance framework, including the policies, standards, decision rights, and guardrails for responsible AI use across the organization

Define standards for approved AI tools, vendors, and workflows, including how capabilities are evaluated, piloted, scaled, and retired

Work with engineering and IT to ensure architecture, integration, security, data, and support requirements are reflected in tooling and product decisions

Maintain guardrails that allow teams to move quickly while preventing fragmented tooling, duplicated effort, and shadow AI use

Partner with HR, Legal, Compliance, and functional leaders to keep governance aligned with how AI is being used across the business

1. Build and manage the enterprise AI portfolio

Identify and prioritize high-ROI use cases across operations, customer delivery, finance, and HR, maintaining a portfolio and backlog that balances business value, user needs, and technical feasibility

Translate priority use cases into product requirements, roadmaps, and delivery plans, and work with engineering and IT to manage priorities, dependencies, and implementation

Manage delivery across cross-functional workstreams, resolving trade-offs and keeping initiatives on schedule through launch and adoption

Build reusable AI workflows, prompts, and playbooks so common needs are solved once and adopted consistently across teams and geographies

Drive adoption through training, documentation, and internal showcases, and give leadership clear visibility into outcomes through adoption, time-saved, quality, and cost metrics

Requirements

What you'll bring

6 to 10 years in consulting, operations, transformation, product, or solutions engineering, including at least two years deploying AI in a commercial or operational setting

Experience leading or contributing to an AI or transformation program from design through implementation

Experience with LLMs, AI agents, automation platforms, prompt engineering, and retrieval-augmented workflows

Hands-on experience using agentic coding tools to build or prototype independently

Technical depth to translate business problems into requirements engineering and IT teams can act on, and technical constraints into decisions business leaders can make

Strong product management skills, including prioritization, requirements definition, roadmap and schedule management, and the ability to balance business, client, engineering, and IT demands across cross-functional workstreams

Proven ability to translate AI into business outcomes across time, cost, quality, and speed

Comfortable coaching executives and challenging traditional ways of working

Executive-level communication, written and verbal

Comfort working across US and Asia time zones

Supply chain or logistics background, consulting experience, or a degree in AI, Computer Science, or Data Science is a plus, but not required.