What are the responsibilities and job description for the AI ENABLEMENT LEAD position at Century Distribution Systems, Inc?
Description
Description
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.
- 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
- 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
- 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.