AI-Native Solution Engineer

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.

· 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.