AI-Native Solution Engineer (Phoenix)

Phoenix, AZJob TypeFull-timeDescriptionRole purpose Own NavPro’s AI-native pre-sales execution end-to-end: improve sales ops efficiency, accelerate product–market fit learning, define solutions for complex fleet deals, and drive the loop from roadmap ? implementation ? measurable outcomes. Demos are a core lever, but the role is accountable for the full technical-commercial motion from discovery through launch readiness. Key responsibilities Run customer-facing NavPro demos:· Lead demos end-to-end, tailored to the customer’s fleet workflow. · Position value, handle objections, and keep the technical narrative accurate. Own discovery ? solution narrative:· Partner with Sales on discovery. · Translate customer needs into a clear demo story and recommended solution approach. Technical validation and execution support (AI-native):· Validate integration feasibility quickly (auth, permissions, data flow, edge cases). · Create lightweight prototypes or API proof-of-concepts when needed (for example, Postman/curl, small scripts). · Provide clear technical guidance to Sales and Product on feasibility, scope, and implementation paths (without owning day-to-day customer support). Maintain demo systems and assets:· Maintain demo environments, scripts, assets, and an industry case library. · Keep examples current with latest product capabilities and limitations. Cross-functional alignment and feedback loop:· Align with Product/Engineering on capability boundaries. · Ensure external commitments are accurate. · Capture common blockers and requirements from demos and feed into the product pipeline. Product ownership for PMF (field-led):· Own a clear PMF learning agenda for NavPro fleet workflows, grounded in sales motions and onboarding reality. · Define and track PMF signals (activation, retention, expansion, usage depth, time-to-value, NPS/CSAT proxies) and review them regularly with Product. · Turn deal-cycle and customer feedback into prioritized product bets with crisp problem statements, impact sizing, and acceptance criteria. · Partner with Product Managers to validate solutions via pilots, pre/post metrics, and a closed-loop feedback process. · Ensure learnings are captured in a repeatable playbook (what works, for whom, and why). Knowledge sharer:· Create internal enablement materials and run training for Sales/CS. Use AI to accelerate work:· Generate tailored demo scripts and talk tracks. · Draft follow-ups, technical summaries, and next-step plans. · Produce competitive and objection-handling notes. · Turn call notes into structured product feedback.Requirements· 2–6+ years in pre-sales, solutions consulting, implementation, technical enablement, or product specialist roles. · Strong presentation and stakeholder management skills. · Comfortable with integration concepts: APIs, auth, permissions, data mapping, webhooks, monitoring, incident paths. · AI-forward working style: uses AI daily for preparation, synthesis, writing, and iteration. · Technical execution requirement (one of): · Can write basic code or scripts (Python/Node/SQL) for API tests, data checks, or automation. · Or has an engineering background with hands-on debugging experience. · Excellent writing: can produce crisp customer summaries and internal documentation. What success looks like (first 90 days):· A repeatable demo + discovery flow that improves conversion on complex fleet deals. · A maintained demo library mapped to top industries, objections, and integration scenarios. · Faster technical validation cycles (clear go/no-go for integrations and custom requests). · A steady pipeline of well-formed product feedback from demos that Engineering can action.