Kamiwaza AI - Senior Sales Engineer
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Requirements
• 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.
Responsibilities
• Lead technical discovery and solutioning: Translate ambiguous customer goals into prioritized use cases, success criteria, and an executable validation plan. • Architect and present solutions: Design reference architectures for cloud, on-prem, hybrid, and air-gapped environments. Articulate the data-in-place value proposition against centralization-first alternatives. • Guide customers through Kamiwaza's distributed data and ontology-driven architecture, helping them understand how agents reason across federated, semantically rich enterprise data without moving it in transit. • Build the demo foundation: Develop and maintain reusable demo assets, POC environments, reference architectures, and platform talk tracks. This is a high-priority early deliverable. • Enable the technical win: Work directly with enterprise buyers from initial discovery through POC completion, ensuring success criteria are defined, met, and documented. • Be the customer's voice: Translate field insights into product feedback and partner closely with Product and Engineering on gaps and accelerators. • Support post-sale handoff: Transfer knowledge cleanly to delivery teams and ensure implementation success.
Benefits
• Purpose & Impact: Be a key contributor to the GenAI revolution, shaping how enterprises adopt next-generation technology. • Remote-First Culture: Based in Colorado, but work from anywhere with the tools and support you need. • Expert Founders with Successful Exits: Our leadership team brings experience and a relentless enthusiasm for GenAI innovation. • High-Autonomy Environment: Flat organizational structure, transparent communication, and minimal red tape. • Competitive Compensation & Equity: Own a piece of our high-potential, well-funded startup. • Comprehensive Benefits: Health coverage, remote workspace support, and more.
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