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Lead product strategy and execution for Nash's enterprise logistics platform. Define requirements, own the product lifecycle, run discovery with customers, validate technical solutions, and launch AI-enabled integrations with OMS/WMS/TMS/POS systems. Drive analytics, documentation, and go-to-market enablement while testing AI models and agent features to improve operational workflows and enterprise value.

As a Mid-Market Account Executive, you'll manage the sales cycle to drive new business in the $10K-$100K ARR segment, work with cross-functional teams, and consistently exceed sales quotas.

The Supply Partnership Manager will manage strategic delivery provider relationships, ensuring operational excellence and driving performance by leveraging technical expertise and analytics.

The Logistics Product Manager will manage enterprise accounts, drive adoption, optimize solutions, and ensure customer satisfaction and performance outcomes.

Provide 24/7 technical support for Nash's delivery orchestration platform: investigate platform and integration issues, coordinate P1 incident response, monitor observability dashboards, escalate with actionable context, document resolutions, and support overflow delivery issues to stabilize customer environments.

Investigate and resolve complex platform and integration issues, own escalations to Engineering with clear reproduction and impact assessment, coordinate P1 incidents, monitor Datadog and observability signals, document resolution patterns for the knowledge base, and provide overflow support for Delivery Support.

Lead deep technical discovery with enterprise customers to design, validate, and sell tailored logistics solutions. Own demos, POCs, integrations, and ROI modeling; present recommendations to executive buyers; test and apply new AI features; and codify repeatable discovery and value frameworks for the GTM team.

Lead technical discovery and design integrations between Nash and enterprise systems. Build demos, sandboxes, scripts, and POCs; validate architecture, security, and reliability through the sales cycle. Test AI models, agents, and APIs; identify failure modes and turn capabilities into customer workflows. Troubleshoot integrations, produce reproducible bugs and requirements, and create reusable tooling and playbooks to scale the Solutions Engineering function.

Lead end-to-end data science initiatives across pricing, dispatch, ETA, routing, and forecasting. Turn ambiguous logistics problems into production ML solutions, build data pipelines, partner with engineering to deploy models, establish evaluation and A/B testing, and work directly with customers and leadership to measure business impact.

Ship, deploy, and operate production backend and integration systems for enterprise logistics. Work directly with customer engineering and ops, take products from concept to live, design core infrastructure, debug real-world workflows, and partner with product and AI teams to scale APAC deployments.