Enterprise AI Product Lead

Job Description

Agilent inspires and supports discoveries that advance the quality of life by providing life science, diagnostic and applied market laboratories worldwide with instruments, services, consumables, application and both measurement and asset management expertise.

Agilent inspires and supports discoveries that advance the quality of life by providing life science, diagnostic and applied market laboratories worldwide with instruments, services, consumables, application and both measurement and asset management expertise.

The single point of contact for value, scope, and adoption across the pod's use case, and the pod's leader in practice. The Product Lead is the interface to the business sponsor and the person accountable for the use case landing in real workflows, operating two-in-a-box with the business domain lead. Expert-led AI is the operating principle: the domain experts frame the work, and the Product Lead ensures the pod builds what they framed rather than what was easiest to demo.

This is a high-autonomy role. The Product Lead operates a small senior team embedded far from the spine, owns a relationship with a VP-level sponsor, navigates the use case's RACI including Legal, Quality, and IT/Security dependencies where they sit on the critical path, and is expected to surface bad news early and kill criteria honestly. The role carries the pod's dual mandate personally: ship business value, and produce reusable Fabric assets, with neither traded away for the other.

• Use case definition and KPI targets, agreed with the business sponsor at approval and tracked honestly through delivery; this includes owning the kill criteria written at approval and recommending a kill or pivot when the data says so.
• Scope, sequencing, and the pod backlog: what gets built, in what order, and what explicitly does not, with trade‑offs surfaced to the sponsor rather than absorbed silently.
• Alignment across the pod and with the spine: the Product Lead is the dotted‑line lead for the pod's engineers and the escalation path for dependencies on the data plane, the harness plane, and the cross‑functional gates.
• Stakeholder management for the use case's RACI, including the Legal and Quality gates on regulated use cases; the Product Lead keeps those gates moving by engaging them early, not by routing around them.
• Adoption and value realization: intelligence shipped into the workflow, used by the named experts, with measured outcomes and adoption telemetry; not a demo that impressed a steering committee.
• The pod's contribution to monthly portfolio review: honest status, measured value, named reusable assets, and what the spine needs to unblock.

• The pod's use case delivering against its committed KPI targets, with value measured in the sponsor's vocabulary and accepted by the sponsor, not only by the CoE.
• Adoption demonstrated by named domain experts using the capability in their daily workflow, with telemetry that distinguishes real usage from launch‑week curiosity.
• At least one reusable Fabric asset from the pod named, certified, and consumed or queued for consumption by another use case.
• A business sponsor who would fight to keep the pod, and a pod team that would follow this Product Lead to the next domain.
• Primary owner of an enterprise AI solution responsible for managing the full solution lifecycle—from ideation and planning through development, deployment, and continuous iteration.
• Acts as the central point for user experience, agile delivery, and cross‑functional coordination across design, engineering, QA, and deployment teams.
• Defines and evolves product features based on user feedback, market research, and emerging technology trends.
• Develops and…