Senior Product Manager, AWS Neurosymbolic AI

About the role

The AWS Neurosymbolic AI team is pioneering the integration of formal reasoning and neural approaches to build AI systems that are not only powerful, but provably correct. We sit at one of the most compelling frontiers in computer science: the convergence of neural networks and symbolic reasoning, where large language models meet theorem provers, and where probabilistic intelligence meets mathematical certainty.

Responsibilities

• Own feature definition and delivery for a specific product area within the neurosymbolic AI platform
• Engage directly with customers and beta participants to understand needs, gather feedback, and validate solutions
• Write clear product requirements and specifications that translate customer problems into buildable scope
• Drive prioritization within your area — making tradeoffs between customer asks, technical debt, and new capabilities
• Partner closely with engineering and science teams through the full development lifecycle
• Define and track success metrics for your features and surface learnings to inform broader product direction
• Contribute to launch readiness — documentation, enablement materials, and go-to-market support
• Communicate progress, blockers, and customer insights to leadership and cross-functional partners

Requirements

Bachelor's degree in Computer Science, Engineering, or a related technical field
5+ years of technical product or program management experience
2+ years of enterprise scale infrastructure or development-based cloud programs/projects in a related industry experience
Experience driving feature delivery end-to-end — from requirements through launch
Strong written communication — you can write a product spec that engineers want to build from

Qualifications

• Experience in identifying a customer need, building a product to meet that need, and launching that product
• Experience shipping innovative, successful consumer products
• Master's degree in a technical field
• Familiarity with formal methods, compilers, programming languages, or verification tools
• Comfort working alongside scientists and engineers on technically complex products
• Experience with usage metrics, A/B testing, or data-driven product decisions