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Kong is seeking a Staff Solutions Engineer to serve as a trusted technical advisor helping enterprise customers architect secure, scalable API ecosystems while navigating the transition to agentic AI. You'll sit at the intersection of API management and AI connectivity, translating Kong's platform capabilities into customer value.
Key Responsibilities:
- Support field sales by helping customers understand Kong's API and AI connectivity platform value proposition
- Conduct discovery conversations to map customer requirements to Kong solutions, from initial reviews through production deployment
- Own technical validation and stakeholder alignment throughout proof-of-concept evaluations
- Ensure customer satisfaction across your assigned account portfolio
- Collaborate with support, product, and engineering teams to advocate for customer needs and influence product direction
- Create technical documentation for DevOps, implementations, and services engagements
- Lead API Management and AI Governance evaluations, including scoping 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 to validate Kong's fit for modern and AI/agentic architectures
- Own technical strategy for complex, multi-stakeholder enterprise deals from qualification through close
- Mentor and coach junior Solutions Engineers on technical skills, discovery methods, and deal strategy
- Drive thought leadership through technical blogs, webinars, speaking at industry events (AWS re:Invent, Google Next, API & AI summit, regional events)
- Synthesize customer feedback and market signals into actionable product input
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 Solutions Engineers or technical team members
- Hands-on 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) — 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 communication and listening skills; ability to 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
