Forward Deployed Engineer

About the role

ARE YOU INTERESTED IN JOINING AN INNOVATIVE LOGISTICS TECHNOLOGY COMPANY?

Loadsmart is a growth-stage technology company valued at over $1 billion (a true Tech Unicorn)!

We are a collection of industry veterans and user-centered engineers using innovative technology to fearlessly reinvent the future of freight by helping shippers, brokers, warehouses and carriers to move more with less.

With headquarters in Chicago and a globally distributed remote team, Loadsmart continues to attract top talent committed to driving meaningful change. We seek professionals who embody our core values: curiosity, clarity, results, commitment, and teamwork.

We're looking for an independent, pro-active thinker, technically sharp Forward Deployed Engineer to join our team. We're looking for someone who's as comfortable writing production code as they are sitting in a room with an operations stakeholder who doesn’t care about architecture but focuses on what works for the business.

This role sits at the front line of Loadsmart's AI-driven automation work. You'll take AI agents and workflows - built on our brokerage, dock scheduling, and shipper platforms and make them actually work in production: for a specific team, a specific workflow, and a specific set of real-world edge cases. You'll build the integrations, tune the AI behavior, and ship working software fast, then feed what you learn back into the platform so it doesn't have to be rebuilt from scratch next time.

LOCATION: US Remote with travel up to 50% to client engagements and Loadsmart's Chicago office.

TEAM: R&D

Job Type: Exempt

WHAT YOU GET TO DO: -

Shadow client teams and their day-to-day operations to see workflows firsthand, then run structured discovery to identify and prioritize the pain points worth solving.

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Design the right solution for each prioritized pain point - whether that's an automation, an AI agent, a system integration, or a combination - and scope it before building.

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Build and integrate that solution against real systems, including transportation management systems (TMS), warehouse management systems (WMS), and enterprise resource planning (ERP) platforms.

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Prototype and ship working automation - such as automated check calls and shipment tracking, carrier qualification and onboarding flows, and voice or chat-based agents - prioritizing action and execution speed to deliver value.

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Tune prompts, agent behavior, and voice or transcription models based on real production data and edge cases - and keep refining after launch, since agent behavior surfaces new edge cases as real usage grows.

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Identify security, compliance, and infrastructure requirements early in each project, and work with the right internal stakeholders to resolve them before they become blockers.

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Feed what you learn back to product and supporting engineering teams, turning recurring patterns into reusable platform capabilities rather than one-off fixes.