Remote AI Product Owner: Agentic Systems & SAFe

Quantiphi

Chicago (IL)

On-site

USD 140,000 - 190,000

Full time

4 days ago
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Job summary

Quantiphi, an AI-first digital engineering and consulting company, seeks a seasoned Product Owner to shape and drive the AI/ML innovation roadmap. You will bridge research and enterprise execution, translating frontier AI concepts into structured epics and stories for cross-functional teams in a SAFe environment.

Based in the USA (Chicago) with remote options, you will collaborate with researchers, data engineers, cloud architects, and executives to scale deployments on GCP and Kubernetes,

Qualifications

  • 10–12 years of professional experience with a strong Product Owner background.
  • Experience with AI/ML products and generative AI.
  • SAFe Agile experience with backlog, PI planning, and dependency management.
  • Ability to translate AI research into epics, features and stories for execution.
  • Proven track record in cloud-native environments and scalable architectures.

Responsibilities

  • Define and drive the AI/ML roadmap and product vision.
  • Manage the innovation backlog balancing risk, viability, and business impact.
  • Translate breakthroughs into actionable epics, features, and stories.
  • Collaborate with researchers, data engineers, cloud architects, and executives.
  • Ensure scalable, secure deployments on GCP/Kubernetes and support CI/CD with GitHub Actions.

Skills

Product Owner
SAFe Agile
AI/ML
Backlog grooming
Stakeholder management
Roadmap planning
Epics & stories
Cross-functional leadership
Architecture discussion

Tools

GCP
Kubernetes
GitHub Actions

Job description

Quantiphi, an AI-first digital engineering and consulting company, seeks a seasoned Product Owner to shape and drive the AI/ML innovation roadmap. You will bridge research and enterprise execution, translating frontier AI concepts into structured epics and stories for cross-functional teams in a SAFe environment.

Based in the USA (Chicago) with remote options, you will collaborate with researchers, data engineers, cloud architects, and executives to scale deployments on GCP and Kubernetes,

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