Enterprise AI Product Lead

Hace 7 días

Barcelona, Cataluña, España Jobrapido Jornada completa
OverviewAumente sus posibilidades de llegar a la fase de entrevista leyendo la descripción completa del puesto y enviando su solicitud sin demora.

In this role, you own the end-to-end success of a high-impact use case within an autonomous pod. You bridge business sponsorship and domain experts to ship real workflow improvements while producing reusable Fabric assets. You operate with a high level of autonomy, aligning cross-functional teams and managing regulatory dependencies to deliver measurable value. You will shape the product to meet sponsor KPIs and drive adoption in daily workflows, not just demos.

Responsabilidades
  • Define use case scope, KPIs, and kill criteria with the business sponsor and track progress through delivery
  • Prioritize and sequence the pod backlog, deciding what to build and what to defer with clear trade-offs
  • Align the pod with the spine and serve as dotted-line lead to engineers, coordinating data plane and cross-functional dependencies
  • Manage stakeholder engagement across the use case RACI, including Legal and Quality gates to keep processes moving
  • Drive adoption and value realization with telemetry to show real usage and outcomes, not just early demos
  • Contribute to monthly portfolio reviews with honest status, measurable value, and reusable assets
  • Own the enterprise AI solution lifecycle from ideation to deployment and iteration
  • Lead cross-functional collaboration (design, engineering, QA, deployment) and ensure user experience is central
Requisitos principales
  • AI-era product management with shipped LLM-application experience
  • Ability to be the single accountable face to a VP-level sponsor while leveraging domain xkdbapo experts as leads
  • Experience operating in a portfolio model with explicit kill discipline
  • Comfort working in regulated environments (GxP exposure a plus)
  • Hands-on fluency in prompting, composing agents, and evaluating AI solutions; able to challenge engineers’ claims
  • humility before domain experts
  • strong stakeholder management
  • openness about issues and bad news
  • LLM-based product management
  • agentic or RAG product development
  • prompt engineering and evaluation