AI-native Partnerships Product Manager

Full-time

Description

Who are we?

Trucker Path is a leading mobile platform built specifically for professional truck drivers and fleets. It offers truck-safe GPS navigation, real-time parking availability, weigh station status, fuel prices, and route planning tools. The platform helps drivers operate more efficiently, reduce costs, and stay compliant on the road.

Role Purpose

Own and deliver Trucker Path’s partner-led growth and marketplace roadmap end-to-end, with a strong bias toward technical execution. This includes fuel as one core program, plus parking and other marketplace offerings that require integrations, shared roadmaps, and reliable delivery.

This is an AI-native role: the PM is expected to use AI daily to speed up discovery, synthesis, writing, analysis, and technical validation, while maintaining high quality and clear accountability.

Key responsibilities

Own marketplace program growth (partner-led): fuel, parking, and more:

· Define strategy, funnel metrics, and quarterly roadmap per program.

· Partner with Growth, Sales, and Ops to ship experiments and measure lift.

· Drive partner-facing alignment on offers, eligibility, tracking, attribution, and reporting.

Own partnerships roadmap across marketplace surfaces:

· Run discovery with partners and internal stakeholders to define needs and success metrics.

· Translate requirements into a prioritized roadmap with clear tradeoffs.

· Coordinate delivery across Product, Engineering, Ops, and partner teams.

Drive integration and technical execution (hands-on):

· Own API and integration readiness: auth, permissions, data flow, edge cases, SLAs.

· Coordinate API specs, monitoring, incident response paths, and post-launch iteration.

· Build lightweight technical prototypes or validation tools to reduce ambiguity.

Operate AI-native product workflows:

· Use AI to synthesize user and partner conversations into crisp problem statements.

· Draft PRDs, API docs, test plans, rollout plans, and stakeholder updates faster.

· Use AI to accelerate analysis (SQL, dashboards, cohort views) and identify levers.

· Create reusable playbooks and templates (launch checklists, partner FAQ, enablement).

Measure outcomes and iterate:

· Define and track success metrics (adoption, conversion, retention, revenue, ops load).

· Run weekly review loops and propose iteration plans based on data and feedback.

Requirements

· 3+ years in product management, ideally across platform, integrations, B2B, payments, or growth surfaces.

· Strong product judgment: can break down ambiguous problems and ship pragmatic solutions.

Technical execution capability required:

· Can work directly with APIs (REST/JSON), auth (API keys/OAuth), webhooks, and basic networking concepts.

· Can write and debug code for prototypes and internal tools (Python, JavaScript/TypeScript, or similar).

· Can query data (SQL) and produce lightweight analyses to validate hypotheses and monitor launches.

· Strong communication skills in English; can align engineers, non-technical stakeholders, and external partners.

· Strong program management across multiple stakeholders, dependencies, and timelines.

· AI-native working style: uses AI daily for research, synthesis, writing, analysis, and automation, while validating outputs with data and technical evidence.

· Familiarity with the U.S. trucking industry, or ability to ramp quickly through user and partner conversations.

Preferred requirements:

· Experience with fuel ecosystems, payments, loyalty, marketplaces, or B2B platform partnerships.

· Experience shipping third-party integrations and owning post-launch monitoring, incident patterns, and iteration.

What success looks like (first 90 days):

· Marketplace growth roadmaps (fuel, parking, and at least one additional program) are defined, instrumented, and shipping measurable improvements.

· A clear partnerships roadmap that sequences integrations and launches with aligned stakeholders, timelines, and success metrics.

· Reduced ambiguity for integrations: clean specs, faster validation cycles, fewer launch surprises.

· A repeatable AI-native operating cadence (docs, updates, analysis, launch playbooks) that increases execution speed without sacrificing quality.