Field-Facing Product Manager, AI for Enterprise

AMAZON WEB SERVICES SINGAPORE PRIVATE LIMITED

Singapore

On-site

SGD 120,000 - 180,000

Full time

5 days ago
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Job summary

Amazon Web Services Singapore Private Limited is seeking a field-facing Product Manager embedded inside an Forward Deployed Engineering delivery pod. You will own the product lifecycle for customer engagements, from discovery through production delivery, working with enterprise customers under compressed timelines.

You will collaborate with engineering to ship production systems, translate engagement learnings into platform improvements, and own the why and what for your engagements while

Qualifications

  • 5+ years in product management, with experience in enterprise environments.
  • Experience in building AI/ML products or working with agentic systems and enterprise workflow automation.
  • Experience defining product requirements, writing product specifications.

Responsibilities

  • Partner with sales and senior PMs to perform customer discovery and map goals, landscape and problems worth solving.
  • Own customer outcomes, define minimum lovable product, and drive production delivery in constrained environments.
  • Contribute to the product/engineering roadmap by surfacing deployment issues and feedback from field delivery.
  • Build domain expertise within engagement vertical and document repeatable patterns for future use.
  • Provide field input on pricing, positioning, and deliverables to sales and marketing partners.

Skills

Product management
Enterprise environments
AI/ML products
Requirements writing

Education

Bachelor's degree in CS/Engineering/Analytics

Job description

Amazon Web Services Singapore Private Limited is seeking a field-facing Product Manager embedded inside an Forward Deployed Engineering delivery pod. You will own the product lifecycle for customer engagements, from discovery through production delivery, working with enterprise customers under compressed timelines.

You will collaborate with engineering to ship production systems, translate engagement learnings into platform improvements, and own the why and what for your engagements while

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