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 at scale. We 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. Our team includes original contributors to the Lean theorem prover and is 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. AWS pioneered the use of formal methods in cloud infrastructure, from network reachability analysis to cryptographic protocol verification to access policy reasoning, systems that serve hundreds of millions of customers today. Now we're taking the next giant leap: fusing that heritage with frontier AI to make every AI system verifiable, trustworthy, and safe. The science innovations developed by this team already power products in customers' hands: Automated Reasoning Checks in Amazon Bedrock Guardrails, policy verification in Amazon Bedrock AgentCore, 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.
What we're building
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.
This is early, high-impact work with direct visibility to AWS's most senior leaders. The customers you'll serve span from Fortune 100 enterprises betting their businesses on AI, to the developer communities building the next generation of autonomous software. You'll be shaping products that define how the world builds trustworthy AI for the next decade.
Key job responsibilities
The Role
As a Technical Product Manager on the AWS Neurosymbolic AI team, you will own the feature definition, customer engagement, and delivery for a focused product area within our neurosymbolic AI platform. You'll work closely with scientists and engineers to turn capabilities into features that customers love — defining requirements, running betas, synthesizing feedback, and driving iterative delivery.
You'll be the connective tissue between what we can build and what customers need. That means spending real time with customers understanding their workflows and pain points, writing crisp product specs that engineering can execute against, and ensuring that what ships actually solves the problem. You should be comfortable going deep on technical details — understanding formal specifications, verification workflows, or managed service architectures — while always keeping the customer experience front and center.
Key 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
About the team
Who Thrives Here: We're looking for 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.
Inclusive Team Culture: The best ideas at the intersection of AI and formal reasoning come from people with different backgrounds and training: mathematicians who became engineers, systems programmers who fell in love with type theory, researchers who wanted more than approximate answers. If your path has been nonlinear, you'll fit right in. We actively seek a diversity of perspectives because the problems demand it.
Training & Career Growth: You'll work alongside an industry-leading team of scientists and engineers who are defining a new field. We invest in growth, attending and publishing at top conferences, collaborating with university research partners, and creating the space to go deep on genuinely hard problems. This is a team where you'll learn constantly, from colleagues who are among the best in the world at what they do.
Work/Life Balance: Deep thinking requires rest, recovery, and a life outside of work. Flexible work arrangements are part of our culture, and we trust our team to manage their time and energy. When we feel supported in the workplace and at home, there's nothing we can't achieve.
Why Join Now? The convergence of large language models and formal reasoning is happening now. It will reshape how software is built, verified, and trusted, and we have the heritage, the talent, and the backing of AWS to lead it. The people who join this team today will define this field for years to come.
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