Own customer value cases. Build value propositions grounded in the customer's actual network and freight data (lane economics, fleet sizing, utilization) and present them to VP/C-level audiences at carriers, shippers, and private fleets.
Speak TCO at the line-item level. Tractor lifecycle, depreciation and residuals, driver cost structures, fuel, insurance, maintenance, empty miles, cost-per-mile vs. cost-of-ownership — and clearly articulate the cost impact of autonomy against the customer's current operating reality.
Hold your own in operational discussions. Responsible for quickly comprehending customer's supply chains, pain points and areas of opportunity. Propose solutions that fit within their desired operating model
Support customer hosting. Partner with your Commercial sales counterpart to run demos, on-sites, and multi-day working sessions as the face of the solutions engagement, owning both the room and the agenda.
Shape the commercial constructs behind a pilot. Work with Sales, Product, and Finance on the structures behind a signed pilot, and with Operations on what can actually be committed and when.
Build with AI tooling. Use Claude Code / Codex daily to build and extend analysis pipelines, models, and customer deliverables in a shared codebase.
Scale the playbook. Turn one-off analyses into repeatable frameworks so each new customer engagement is faster than the last. As the team grows, help shape it — mentoring future hires and building out the function
10+ years in trucking or logistics, with deep exposure to fleet operations or truck OEMs — carrier network and pricing leadership, fleet management, or OEM vocational/TCO sales engineering (or a comparable path).
Direct experience in the Class 8 equipment lifecycle — buying, selling, or leasing.
A demonstrated record of building and presenting quantitative value propositions and business cases to senior executives.
Strong quantitative modeling skills, with the ability to apply them inside an agentic coding environment.
Autonomous vehicle or fleet-tech exposure strongly preferred.
Executive presence — sharp storytelling, strong deck craft, and the judgment to know what belongs on a slide and what doesn't.
Integrity under commercial pressure — holds the line on what the technology and the timeline can and cannot support.
Comfort operating in ambiguity — early-commercial-stage motion, evolving pricing, no established playbook.
Experience with freight data — TMS extracts, rate benchmarks (e.g., DAT), network optimization.
Working, current fluency with AI coding agents (Claude Code, Codex, or equivalent).
Prior experience in consulting or solutions engineering.
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