Forward Deployed Engineer

Loadsmart•Chicago, IL

68d•$115,700 - $180,800•Remote

About The Position

Loadsmart is seeking an independent, pro-active, and technically sharp Forward Deployed Engineer to join their R&D team. This role is crucial for Loadsmart's AI-driven automation initiatives, focusing on taking AI agents and workflows from development to production. The engineer will be responsible for making these AI solutions functional for specific teams and workflows, handling real-world edge cases. Key activities include building integrations, tuning AI behavior, and rapidly shipping working software. The learnings from this role will be fed back into the platform to improve future development. The position is US Remote with up to 50% travel to client engagements and Loadsmart's Chicago office.

Requirements

5+ years of full-stack engineering experience, with strong proficiency in Python and TypeScript, including supporting libraries and frameworks that leverage fast prototyping.
Hands-on experience designing and implementing automated workflows and AI-driven solutions to optimize business processes.
Proven experience building and maintaining APIs and integrations with third-party or enterprise systems.
Demonstrated ability to work directly with non-technical stakeholders â€” translating operational needs into technical solutions, and clearly explaining technical trade-offs and progress, both in writing and in conversation.
Comfortable being the person in the room when things don't go as planned â€” able to debug, re-scope, or improvise a solution in front of a customer rather than escalating and waiting.
A track record of shipping working software quickly in ambiguous, fast-changing environments.

Nice To Haves

Experience with voice or transcription-based systems, especially in operational or logistics contexts.
Familiarity with freight, transportation, or supply chain systems (TMS, WMS, or ERP platforms).
Experience working in a growth-stage or startup environment where the platform underneath your work is still being built.
Exposure to agent orchestration frameworks or evaluation/monitoring tooling for LLM-based systems.
Prior experience in a role that required both building software and owning a customer relationship.

Responsibilities

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.
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.
Build and integrate that solution against real systems, including transportation management systems (TMS), warehouse management systems (WMS), and enterprise resource planning (ERP) platforms.
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.
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.
Identify security, compliance, and infrastructure requirements early in each project, and work with the right internal stakeholders to resolve them before they become blockers.
Feed what you learn back to product and supporting engineering teams, turning recurring patterns into reusable platform capabilities rather than one-off fixes.