Jobs at Kong

Design and build scalable distributed backend systems and core services in Golang. Develop reliable, high-performance systems using PostgreSQL and Redis across microservices, networking layers, and cloud platforms. Prototype and productionize platform capabilities, collaborate on strategic technical initiatives, and influence engineering standards. The role focuses on AI infrastructure, distributed database provisioning, workflow orchestration, internal tooling, and developer experience.

Manage a portfolio of commercial customers throughout their lifecycle, driving adoption, customer outcomes, and growth. Partner with Sales, Product, and Customer Experience teams to develop adoption plans, improve engagement, and deliver innovative technical projects. Serve as a Kong product subject matter expert, helping customers apply APIs, microservices, AI, Kubernetes, cloud-native technologies, DevOps, and CI/CD. Identify opportunities for automation, self-service tooling, and reusable customer-success processes.

Source and headhunt top GTM talent for the CRO organization, partner with GTM leaders to define role requirements, conduct deep-dive competency interviews focused on deal mechanics, drive a rigorous interview process, provide market data and advise hiring managers, mentor other recruiters, and track conversion metrics to optimize the hiring funnel.

Source and assess high-caliber go-to-market talent for Kong’s CRO organization. Responsibilities include mapping competitor sales teams, conducting targeted headhunting, advising GTM leaders, providing market compensation data, performing competency interviews focused on sales deal mechanics, improving interview funnel metrics, and mentoring recruiters on GTM terminology and closing strategies.

The Director of Scaled Customer Success will lead a global team to innovate and implement a digital-first customer success strategy, enhancing customer engagement through automation and AI-driven experiences.

Embed with business teams to design and build AI-powered tools, automations, and workflows; coach and enable staff; create reusable solutions, documentation, adoption metrics, and governance; mentor junior members and translate AI developments into practical enterprise applications.