AI Product Lead, Enterprise Operations & Transformation

Alta Genetics

Oregon

Ibrido

USD 120.000 - 180.000

Tempo pieno

5 giorni fa

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Descrizione del lavoro

URUS is seeking an AI Product Manager for Enterprise Operations to translate complex business challenges into practical, AI-enabled solutions. You will partner with Commercial, Finance, People, and other functions to identify high-value use cases, develop business cases, and guide solutions from discovery through adoption and performance measurement.

You will blend product management, process improvement, and change leadership with hands-on AI knowledge to assess value, risk, and feasibility

Competenze

Bachelor's degree in business, technology, computer science, data science, engineering, or related field, or equivalent experience.
At least three years of experience in product management, business transformation, process improvement, or a related role.
Experience delivering AI/ML-enabled products, workflows, automation, or internal tools from discovery through adoption.
Product ownership experience with roadmaps, backlogs, user stories, acceptance criteria, and prioritization.
Ability to analyze business processes and translate needs into practical technology solutions.
Experience developing business cases and measuring outcomes such as ROI, cost savings, productivity, quality, or user adoption.
Experience leading cross-functional initiatives with business and technical stakeholders.
Experience supporting organizational change through adoption planning, training, and feedback.
Practical knowledge of generative AI, large language models, AI-enabled automation, and emerging agentic capabilities.
Strong communication skills for nontechnical audiences.

Mansioni

Partner with business leaders and functional teams to uncover operational challenges and AI opportunities.
Evaluate and prioritize AI opportunities based on impact, feasibility, data readiness, risk, adoption effort, and alignment.
Develop problem statements, business cases, product requirements, user stories, acceptance criteria, and success metrics.
Own and refine the AI product roadmap and backlog, prioritizing and sequencing work for execution.
Guide AI-enabled solutions from discovery through MVP, production release, adoption and measurement.
Collaborate with AI engineers, data scientists, architects, PMs, stakeholders, and partners to design solutions.
Assess data readiness, governance, privacy, security, model quality, and long-term support before production.
Lead adoption through engagement, training, documentation, and feedback.
Establish performance measures linking AI initiatives to outcomes like efficiency and ROI.
Communicate priorities, progress, risks, tradeoffs, and recommendations to leaders.