Staff Product Manager, AI Management

About the Role:

Kong is building the future of AI connectivity, empowering developers to connect, secure, govern, and scale their AI applications with speed and intelligence. Kong's AI Management solution – including our flagship AI Gateway – is one of our most strategic and fastest-growing product areas, and we're growing the team to match.

We're looking for a Staff Product Manager to join the AI Management product team, based in our Milan office. You'll be the product owner for some of our most exciting, fastest-growing agentic AI management and infrastructure products.

You'll work in close partnership with the broader AI Management research & development team, with a focus on driving definition and delivery of features and cross-team product work, collaborating with product managers and engineers around the world, while also supporting the field activities, including product marketing, sales, and enablement. This is a high-impact, hands-on product management role that reports directly to our Director & Head of AI Products.

What You’ll Own:

• AI Management Product Modules: Own the product direction for AI Management product modules that help connect, govern, supervise, and optimize agentic AI, including models, context, agentic harnesses, guardrails, evaluation, policies, and more. You'll define requirements, write specs, prioritize the backlog, and drive delivery of your module’s features in close collaboration with engineering.

• Cross-Product Infrastructure & Dependencies: Drive the cross-product work that connects your AI Management modules to other modules within AI Management, as well as Kong’s broader platform. You'll navigate shared roadmaps, negotiate priorities across teams, and ensure AI Gateway's infrastructure needs aren't blocked by cross-team complexity.

• Roadmap & Delivery: Own a clearly defined product roadmap for your areas, balancing new feature development against technical debt, infrastructure work, and platform dependencies. You'll partner with engineering leads to scope work, make trade-off decisions, and maintain a reliable delivery cadence.

• Stakeholder Communication: Serve as the connective tissue between engineering, design, product marketing, and leadership for your areas of ownership. Keep stakeholders informed, surface risks early, and ensure alignment across time zones and teams.

• Field Support: Support regional field activities as needed — such as customer-facing calls, product marketing input, or sales enablement — particularly where your proximity in Shanghai and knowledge of the runtime add value.

You’ll Thrive in This Role If You:

• Have 7-10 years of product management experience, with a track record of owning and shipping technical products — ideally in agentic AI, infrastructure, developer tools, and/or platform software.

• Have experience driving product delivery across distributed teams — you're comfortable working across time zones, navigating dependencies between teams, and keeping things moving without having direct authority over every contributor.

• Are strong at translating ambiguous technical problems into clear product requirements — you can take a messy infrastructure challenge, break it down, and turn it into a spec that engineering can execute against.

• Communicate clearly and proactively — you'll be the bridge between globally distributed stakeholders, across multiple functions and levels of seniority, so strong written and verbal communication in both languages is essential.

• Have solid project management instincts — you may not be a full-time project manager, but you know how to track work, surface blockers, and keep a roadmap on track without being asked.

• Are comfortable engaging with technical depth — you don't need to write code, but you should be able to hold your own in conversations about MCP servers, transport protocols, request routing, data plane architecture, and infrastructure trade-offs.

• Bonus: Direct experience with agentic AI development and products, including AI agents, AI gateways, and related infrastructure (e.g. LLM routing, AI observability, prompt management & guardrails, MCP servers, A2A, and various cost and quality optimizations).

• Bonus: Familiarity with enterprise platform engineering and infrastructure, including data planes, control planes, Kubernetes, cloud-native architectures, and/or platform engineering workflows.

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