AI-Native Solution Engineer

Apply Job Type: Full-time Description: Role 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.