Solutions Engineer

The Role

This is a foundational technical hire at Nash, an autonomic logistics platform that helps enterprises plan, execute, and manage deliveries across their own fleets, third-party partners, and the Nash delivery network. We’re building out our Solutions Engineering function and need someone who can understand complex systems, build working solutions, and explain them clearly to customers.

You’ll lead technical discovery, review API documentation and sample data, map integrations, configure demos and test environments, and run POCs with enterprise prospects. You’ll also test new models, agent capabilities, APIs, and Nash features as they ship, understand where they work and where they break, and turn the strongest applications into practical customer workflows.

Our customers are large enterprises operating fleets across regions, fulfillment channels, and dozens of existing systems. You’ll need to understand how orders, inventory, dispatch decisions, delivery updates, and exceptions move through that environment, then show exactly how Nash fits into it.

What You'll Own

• Lead technical discovery: Work with customer engineering, IT, and operations teams to understand their current systems, workflows, data, business rules, constraints, and failure points.

• Design the solution architecture: Turn those findings into a clear integration plan for Nash, including system connections, endpoints, payloads, authentication, webhooks, data ownership, error handling, and required changes.

• Build technical demos and POCs: Configure realistic sandboxes, prepare customer data, write lightweight scripts, connect APIs, and build prototypes against agreed success criteria.

• Own technical validation through the sales cycle: Address architecture, integration, security, data, reliability, and scalability questions. Give customer engineering and IT teams what they need to approve the solution.

• Apply AI to real workflows: Build and test prompts, agents, tool calls, and evaluation sets using realistic scenarios. Measure quality, identify failure modes, and determine whether the workflow is reliable.

• Test new capabilities hands-on: Work with new AI models, agent features, APIs, and product releases as they ship. Build prototypes, test edge cases, document limitations, and identify promising customer use cases.

• Build reusable tooling: Turn repeated work into scripts, test harnesses, sample integrations, demo environments, dashboards, and utilities that accelerate future deals.

• Close the loop with Product and Engineering: Write clear requirements, reproduce bugs, provide sample payloads and logs, and follow through until blockers are resolved.

• Raise the technical bar across GTM: Train AEs on technical fundamentals, mentor future SEs, and build the playbooks and onboarding materials the team will use as it grows.

What We're Looking For

• 4 to 6 years in solutions engineering, presales, technical GTM, growth engineering, or a similar customer-facing technical role, with ownership from discovery through technical validation.

• Hands-on comfort with AI tools and models: you’ve designed prompts, built agents, run evaluations, tested failure modes, and tried new frameworks yourself, not just read about them.

• Real building ability: you can write scripts, transform data, work with APIs, debug integrations, and stand up a sandbox, prototype, or internal tool without waiting for an engineer.

• Fluency with system architecture and integration patterns, including REST APIs, webhooks, authentication, JSON payloads, and data flows across systems such as OMS, WMS, TMS, and POS.

• Experience designing and running technical demos, trials, or POCs with clear requirements, success criteria, and a path to a real customer decision.

• Strong technical discovery skills: you can work across stakeholders to uncover edge cases, dependencies, data gaps, and requirements customers may not articulate.

• Comfort operating in complex enterprise environments spanning multiple regions, channels, workflows, and integrations.

• Ability to turn technical complexity into clear architecture diagrams and explain tradeoffs to engineers, IT leaders, operators, and executives.

• Ownership instinct, strong product judgment, and comfort working through incomplete requirements and ambiguity.

Even better if you have: 2+ years in a sales engineering or growth engineering role; experience shipping AI-native product features or agents into production; experience in logistics, delivery, or supply chain.