Kamiwaza AI - Senior Sales Engineer

• 8+ years in customer-facing technical roles, including 5+ years in Sales Engineering or Solutions Engineering for infrastructure, enterprise software, data platforms, or AI/ML products. • Track record of leading technical wins and building credibility with both technical (CTO, architect) and executive (C-suite) stakeholders. • Genuine fluency in enterprise AI architectures: LLMs, RAG, vector databases, embedding pipelines, evaluation and observability, and agent orchestration patterns. • Working knowledge of distributed data architectures: federated data platforms, data mesh concepts, and the realities of AI across siloed or air-gapped data stores. • Conceptual familiarity with knowledge graphs and ontology-driven data models — enough to position their role in enterprise AI architectures and speak credibly with customer architects. • Demonstrated experience designing for on-prem, air-gapped, and hybrid environments, including security reviews, network constraint conversations, and data sovereignty requirements. • Comfort with enterprise security topics: access control models including RBAC and relationship-based variants, audit and compliance requirements, and how security posture shapes AI deployment decisions. • Executive communication: Confident with C-suite, equally capable whiteboarding architecture with a technical team. Strong written proposals and discovery documentation. • Startup readiness: You've operated in environments where process isn't fully built and you're expected to create it. High autonomy, fast iteration, minimal red tape. • Travel: 20-35% for customer meetings, workshops, and field engagements. • Track record of technical wins on six- and seven-figure deals. • Hands-on experience with knowledge graph platforms (e.g., Neo4j, Stardog) or ontology frameworks (OWL, RDF). • Experience with data catalog, data lineage, or master data management solutions in enterprise environments. • Background in regulated industries: financial services, healthcare, defense, or public sector. • Familiarity with MCP (Model Context Protocol), agentic workflow design, or multi-agent system patterns.