Senior Product Manager, AWS Neurosymbolic AI

Overview

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.

Our mission is to make AI trustworthy  develop technology that enables AI systems to reason rigorously, verify their own outputs, and provide mathematical guarantees about their behavior. This is a fundamental shift in how AI systems are built, and we believe it s on the critical path to the next generation of safe, reliable AI-powered applications. We are one of the strongest concentrations of neurosymbolic AI talent in industry, with team members connected to the Lean theorem prover and advised by Lean s Chief Architect.

We bring together researchers and engineers from both the AI and formal methods communities, a combination that is extraordinarily rare and increasingly essential. We build on Amazon s 10+ year track record of bringing automated reasoning to production at scale, and we are fusing that heritage with frontier AI to make every AI system verifiable, trustworthy, and safe. The science innovations developed by this team power products in customers  hands today, including Automated Reasoning Checks in Amazon Bedrock Guardrails, policy verification in Amazon Bedrock Agent Core, and intelligent specification, testing, and correctness workflows in Kiro.

We publish at top venues, collaborate with leading academic institutions, and operate with the urgency and ownership of a startup inside one of the world s most impactful technology companies. If you re excited by the idea of teaching machines to prove, not just predict, we d love to talk.

We are building a platform that brings the rigor of formal mathematics to the world of AI and software development. Our technology enables developers, AI agents, and autonomous systems to formally verify correctness, enforce guarantees, and establish trust, especially as AI-generated code and autonomous agents become the default, not the exception. The core question we re answering: as AI systems become more capable and more autonomous, how do you know they did what you asked, correctly, safely, and completely?

We re building the answer, using technologies like Lean 4 (the same formal language behind recent breakthroughs in AI mathematical reasoning) combined with state-of-the-art neural approaches. Our platform combines neural networks with formal verification engines, enabling capabilities that neither approach achieves alone: AI that writes code and proves it s correct; agents that act autonomously and guarantee they ll respect constraints;

systems that reason about their own behavior with mathematical precision.

• 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 — balancing 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

Who Thrives Here:
We seek people who defy easy categorization. Engineers who think like product managers. Scientists who care about shipping. Product leaders who can read a paper and sketch a system architecture on a whiteboard. The problems we re solving require people who move fluidly between disciplines, and we ve built a culture that rewards breadth as much as depth.

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