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Lanesurf

Forward Deployed Engineer

Lanesurf, Chicago, Illinois, United States, 60290

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This range is provided by Lanesurf. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range $100,000.00/yr - $150,000.00/yr

Company Overview Lanesurf builds enterprise-grade AI systems for freight operations— that automates how freight is priced, negotiated, and booked.

Our systems run continuously, handling carrier communications, negotiating rates, verifying compliance, and executing load transactions for brokerages and 3PLs that collectively manage

over $10 billion in annual freight.

We’re backed by General Catalyst (~$30B AUM) and Y Combinator (~$800Bn portfolio value) and we are scaling across the U.S. freight network.

About the Role | Forward Deployed Engineer (FDE) As a

Forward Deployed Engineer (FDE) , you’ll operate at the intersection of

engineering, AI, and live customer systems.

You’ll work directly with freight brokerages to deploy, debug, and optimize Lanesurf’s Voice-AI in production — ensuring every call, negotiation, and booking works reliably at scale.

This is a

hands‑on, field‑facing engineering role . You’ll move between writing code, diagnosing live issues, building integrations, tuning models, and translating operational insights into core product improvements.

If you like solving hard, messy, high‑stakes problems where

AI meets real operations , this is that role.

What You’ll Do

Partner directly with customers — from onboarding through production — ensuring Lanesurf’s AI agents deliver measurable results on live freight.

Debug, tune, and optimize

real‑time voice‑AI pipelines

(STT → LLM → negotiation logic → TTS → transport).

Build and maintain lightweight

integrations, automations, and scripts

connecting customer systems (TMS, CRMs, APIs) to our AI stack.

Work closely with

core engineering and product teams

to reproduce, isolate, and resolve field issues rapidly.

Develop

deployment playbooks and reusable frameworks

that make future rollouts faster and more reliable.

Surface insights and edge cases from customer operations to inform

model tuning, UX design, and roadmap priorities.

Represent engineering in the field — communicate clearly with both technical and non‑technical stakeholders.

Ship quickly, iterate aggressively, and

own every deployment like it’s your own product.

What We’re Looking For Required

3–8 years in software engineering, implementation, or customer‑facing technical roles.

Strong proficiency in

Python, Node.js, or TypeScript

— able to build integrations and debug live systems.

Experience with

real‑time APIs, WebRTC, or streaming systems.

Familiarity with

AI/LLM pipelines

— prompting, orchestration, or model tuning.

Clear technical communication and ability to work directly with customer teams under time pressure.

Comfort working in

high‑stakes, production environments

where reliability and speed both matter.

Deep ownership mindset — you care about outcomes, not job titles.

Why Join Us

Proven Traction:

Our AI platform is in production, executing

thousands of live carrier negotiations and load bookings daily .

Institutional Backing:

Funded by

General Catalyst (~$30 B AUM)

and

Y Combinator (~$800 B portfolio value) , giving you the capital base, credibility, and network to win enterprise accounts.

Technical Depth:

Every millisecond matters — work spans audio streaming, distributed inference, and low‑latency transport design.

Founding Scope:

Shape core architecture, define standards, and influence how real‑time AI behaves under production constraints.

Leverage:

Your code directly impacts freight networks managing

billions in annual volume

— measurable, high‑stakes engineering.

Environment Built for Engineers:

Small team, direct access to production systems, fast iteration cycles, and no layers between you and the work.

Seniority level Mid‑Senior level

Employment type Full‑time

Job function Engineering and Information Technology

Industries Transportation, Logistics, Supply Chain and Storage

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