Sr Product Manager, Technical, AWS Forward Deployed Engineering (FDE)

AMAZON WEB SERVICES SINGAPORE PRIVATE LIMITED; Singapore; On-site; SGD 120,000 - 190,000; Full time

Job summary

AMAZON WEB SERVICES SINGAPORE PRIVATE LIMITED is seeking a field-facing Product Manager embedded in Forward Deployed Engineering to own engagements from discovery through production delivery within enterprise customers. You will collaborate with sales and senior PMs, define outcomes, write specifications, and work with engineering to ship production systems under tight timelines.

Travel 30-50% is required. This role emphasizes customer-facing leadership, outcome-driven development, and

Qualifications

• Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent.
• 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 requirements documents, and setting success criteria that align engineering execution with measurable results.
• Experience engaging with Director-level or senior technical stakeholders.

Responsibilities

• Partner with sales and senior PMs to perform customer discovery — mapping business goals, technical landscape, and problems worth solving.
• Engage with Director-level and senior technical stakeholders at enterprise customers to understand how AI technology can address their business challenges.
• Work with engineering to define the minimum lovable product, write success criteria, and quantify expected business value.
• Own customer outcomes for engagements inside customer environments with real constraints — regulated data, brownfield infrastructure, multi-stakeholder governance.
• Follow AI DLC to iteratively define problems, write requirements, and deliver production code in weeks, not months.
• Drive solutions from launch to adoption by capturing user feedback, iterating, and proving defined business value.
• Make judgment calls about what simplifications are acceptable and when a product is ready to ship versus when it needs more iteration.
• Identify what breaks or slows down across deployments and surface findings to senior PMs and engineering.
• Contribute to the feedback loop between field delivery and the product/engineering roadmap.
• Advocate for graduating custom pod work into reusable platform capabilities with supporting data.
• Build domain expertise within engagement verticals.
• Contribute to industry‑specific accelerators, reference architectures, and blueprints that make future engagements faster.
• Document repeatable patterns from your work so solved problems become reusable assets.
• Contribute to customer stories and reference architectures drawn from engagements.
• Provide field‑level input on pricing, positioning, and what it takes to deliver outcomes to sales and marketing partners.

Skills

Product management

Enterprise environments

AI/ML products

Stakeholder engagement

Requirements writing

Education

Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent

Job description

95% of enterprise technology pilots deliver zero measurable P&L impact. The technology works — the gap is in the last mile: getting production systems running inside complex enterprises where legacy infrastructure, regulated data, and organizational complexity collide. AWS is making a billion-dollar investment in Forward Deployed Engineering to close that gap.

You are a product manager embedded inside an FDE delivery pod, owning the product lifecycle for customer engagements — from discovery through production delivery. You work directly inside enterprise customers: performing discovery, defining outcomes, writing specs, managing trade-offs, and working hand‑in‑hand with engineering to ship production systems under compressed timelines.

This is not a traditional AWS PM role. You are field-facing — you work with customers regularly and turn engagement learnings into platform improvements. You own the why and what for your engagements, while engineering owns the how.

Traveling 30-50% is required for this role.

Key job responsibilities

Customer Discovery and Scoping

• Partner with sales and senior PMs to perform customer discovery — mapping business goals, technical landscape, and problems worth solving
• Engage with Director-level and senior technical stakeholders at enterprise customers to understand how AI technology can address their business challenges
• Work with your engineering counterparts to define the minimum lovable product, write success criteria, and quantify expected business value

Product Ownership and Delivery

• Own customer outcomes for your engagements, operating inside customer environments with real constraints — regulated data, brownfield infrastructure, multi‑stakeholder governance
• Follow AI DLC to iteratively define problems, write requirements, and deliver production code in weeks, not months
• Drive solutions from launch to adoption by capturing user feedback, iterating, and proving defined business value
• Make judgment calls about what simplifications are acceptable and when a product is ready to ship versus when it needs more iteration

Platform Feedback

• Identify what breaks or slows down across your deployments and surface those findings to senior PMs and engineering
• Contribute to the feedback loop between field delivery and the product/engineering roadmap
• Advocate for graduating custom pod work into reusable platform capabilities with supporting data

Industry Learning and Reuse

• Build domain expertise within your engagement vertical
• Contribute to industry‑specific accelerators, reference architectures, and blueprints that make future engagements faster
• Document repeatable patterns from your work so solved problems become reusable assets

Go-to-Market Contribution

• Contribute to customer stories and reference architectures drawn from your engagements
• Provide field‑level input on pricing, positioning, and what it takes to deliver outcomes to sales and marketing partners

About the team

ABOUT AWS:

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Basic qualifications

• Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
• 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 requirements documents, and setting success criteria that align engineering execution with measurable results
• Experience engaging with Director-level or senior technical stakeholders

Preferred qualifications

• Master's degree in engineering, statistics, computer science, operations research, business analytics, information systems or equivalent
• Experience delivering production systems inside enterprise customer environments: regulated data, legacy infrastructure, organizational complexity
• Background in field-facing product management — has spent time working directly with customers on deployments from discovery through production launch
• Experience in at least one enterprise vertical: financial services, healthcare/life sciences, manufacturing, telecommunications, or public sector
• Experience with value-based scoping, including quantifying business value (ROI, P&L impact) and defining outcome‑based success criteria

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