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

NextBigWhat; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Amazon Web Services is seeking a product manager embedded in Forward Deployed Engineering, working inside enterprise customers to shape discovery, define outcomes, and deliver production AI/ML solutions. You will own engagements from discovery through delivery, while partnering with engineering to ship under compressed timelines.

This field-facing role requires travel ~30–50% and strong ability to translate customer learnings into platform improvements, with a focus on ROI and measurable

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 PRDs, and setting success criteria.
• Experience engaging with Director-level or senior technical stakeholders.

Responsibilities

• Perform customer discovery and scoping with sales and senior PMs.
• Own customer outcomes inside enterprise environments with regulated data and legacy infrastructure.
• Follow AI DLC to define problems, write requirements, and deliver production code in weeks.
• Drive adoption by capturing feedback and proving business value.
• Contribute to GTM through customer stories and pricing/positioning input.

Skills

Product management

Enterprise engagement

AI/ML product experience

Stakeholder communication

Field-facing delivery

Education

Bachelor's degree in CS/Engineering/Analytics

Master's degree in Engineering/CS/OR/Business Analytics

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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• 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
• 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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