K- Work from
- United States
- Contract
- Full-time
- Experience
- Lead
- Salary
- $222K – $250K / year
- Posted
- 10 November 2026
- Apply by
- 9 January 2027
As a Staff Solutions Engineer at Kong, you won’t just be selling a platform — you’ll be a trusted technical advisor helping the world’s most innovative enterprises architect secure, scalable API ecosystems while navigating the transition into the agentic AI era. Kong sits at the intersection of API management and AI connectivity, and you’ll be the person who makes that story real for customers.
Are you ready to unlock intelligence?
If you don’t think you meet all of the criteria below but are still interested in the job, please apply. Nobody checks every box - we’re looking for candidates that are particularly strong in a few areas, and have some interest and capabilities in others.
About the role
Are you ready to sit at the epicenter of the API and AI connectivity revolution?
Responsibilities
- Support field sales in helping customers understand the value of the Kong API and AI connectivity platform.
- Conduct discovery conversations to understand customer requirements and map them to Kong solutions, from initial product reviews through to production.
- Support POCs throughout the entire evaluation process, owning technical validation and stakeholder alignment.
- Ensure customer satisfaction across your assigned set of accounts.
- Collaborate with support, product, and engineering teams to advocate for customer needs.
- Create technical documentation for DevOps, implementations, and services engagements.
- Lead and support API Management and AI Goverance evaluations, including scoping API/AI use cases, LLM traffic management, and governance requirements.
- Deliver demonstrations of Kong’s API & AI governance and agentic connectivity capabilities, including Model Context Protocol (MCP) governance, semantic caching, prompt guardrails, and shadow AI detection.
- Run API & AI-focused Technical Feasibility Workshops (TFWs) to validate Kong’s fit for modern and/or AI/agentic architectures.
- Own the technical strategy for complex, multi-stakeholder enterprise deals from qualification through close.
- Mentor and coach junior SEs on technical skills, discovery methods, and deal strategy.
- Drive thought leadership by authoring technical blogs, hosting webinars, speaking at industry events and conferences such as AWS re:Invent, Google Next, API & AI summit, and regional events
- Influence product direction by synthesizing customer feedback and market signals into actionable input for the product team.
- And any additional tasks required by manager.
Requirements
- 7+ years of software engineering and/or solutions engineering experience at a SaaS, open source, or enterprise software company.
- Proven track record owning complex, enterprise-level deals with multiple technical and executive stakeholders.
- Experience mentoring or coaching other SEs or technical team members.
- Experience with Docker, Kubernetes, and cloud-native platforms.
- Experience with REST and GraphQL APIs, CI/CD pipelines, and API security patterns (OAuth2, OIDC, mTLS).
- Hands-on experience with AI-assisted development tooling — Claude Code, GitHub Copilot, OpenAI Codex, or equivalent is required.
- Working knowledge of AI/LLM architectures, including model routing, rate limiting, semantic caching, and prompt governance.
- Familiarity with Model Context Protocol (MCP) and agentic AI patterns.
- Solid understanding of cloud computing trends and open source business models.
- Strong listener and communicator — you can confidently lead discussions with engineers, architects, and executives.
- Enthusiasm for working in a high-profile, fast-paced environment at the intersection of API and AI connectivity.
Salary
Compensation Range: $222K - $250K
About Kong
Kong Inc., the AI Connectivity Company, is building the connectivity layer of AI. Trusted by the Fortune 500® and AI-native startups alike, Kong’s unified API and AI platform enables organizations to secure, manage, accelerate, govern, and monetize the flow of intelligence across APIs and AI traffic — on any model, any cloud. For more information, visit.
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