# AI Engineer at Cargomatic > Remote · United States · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/greenhouse%3Acargomatic%3A5207803008 (read 2026-11-08). ## Facts (observed) - Company: [Cargomatic](https://alderhq.app/companies/cargomatic) - Location text: United States; Remote - Where it can be done from (inferred): Remote · United States (evidence: "Location: United States; Remote") - Posted: 2026-05-01 (191 days ago) - First seen by alder: 2026-11-04 · last verified: 2026-11-07 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://job-boards.greenhouse.io/cargomatic/jobs/5207803008 - Skills listed (inferred): Node.js, GraphQL, LLMs ## Pay and sponsorship - Posted pay: $150k–$210k per year (from the description) - Market band for similar posted roles (United States, n 735): p25 $183k, median $224k, p75 $275k ## Description (the employer's text) AI Engineer – Agentic Automation Location: Remote Compensation: $150,000 – $210,000 Reports to: Director of Product Join a rapidly growing company disrupting the trucking industry! Cargomatic is the #1 technology platform and digital marketplace for powering world-class, local trucking. Take a look around you. Literally everything humans build, grow, or sell has spent time on a truck. Local trucking is the lifeblood of every regional economy, and yet this $82 billion industry still relies heavily on phone calls and fax machines. Cargomatic is transforming the way goods move around every local node in the supply chain by connecting shippers and commercial truck drivers with mobile technology. We are solving complex, real-world problems every day, and giving full transparency to the shipping process. About the Role Cargomatic runs a live TMS, an RPA stack, and many manual, exception-heavy logistics workflows across pricing, dispatch, documents, billing, and invoicing. We're looking for a hands-on AI Engineer to automate them. Product identifies and prioritizes the opportunities. You'll determine the right way to automate each one (build, buy, or partner) and deliver it in production, in partnership with our Engineering and Platform teams and following their standards. You'll report to the Director of Product, with dedicated capacity for automation delivery, and work closely with Operations and our RPA team. ### What You'll Do - Build and ship automations and agentic workflows that call our internal REST and GraphQL APIs to read data and take production actions. - Deliver document automation (OCR and extraction) using managed services and LLM vision. This includes confidence thresholds, deterministic validation against TMS data, and routing low-confidence results to human review. - Determine and design the right approach for each workflow: LLM, deterministic software, RPA, or a purchased tool, with clean handoffs between them. - Run build vs. buy evaluations, including POCs and bake-offs covering total cost of ownership, integration effort, and operating burden. Then implement the decision, whether that means building or integrating and rolling out what we buy. - Partner closely with our RPA team (UiPath). Identify existing bots that should be augmented or replaced with AI, and design workflows where AI and RPA hand off cleanly. - Coordinate with Engineering and Platform when automation needs platform changes. Scope the ask clearly, then deliver your side. - Build the evaluation infrastructure for every AI system we ship: labeled datasets, LLM-as-judge pipelines, regression testing, and release gates. Product defines the quality criteria; you make them executable. - Make AI systems dependable through validation, fallbacks, idempotency, permissions, audit trails, monitoring, and capture of reviewer corrections. - Inventory and rationalize our existing low-code automations (Zapier): decide which to keep, harden, consolidate, or replace. Check what our existing stack already covers before adding anything new, and avoid depending on tools we plan to retire. - Prototype quickly against real workflows and data, and take successful work all the way to production. ### Scope This role consumes platform capabilities and does not own core platform, authentication, or infrastructure. Agent infrastructure needs, such as tool authorization and observability, are evaluated for buy or partner options first, in partnership with Engineering and DevOps. Initial document AI work uses managed services; model hosting and training are in scope only if evaluation shows a clear need. All production work follows Engineering's standards: code in our shared repositories, Engineering code review and architecture review, standard deployment and monitoring, and Engineering sign-off on production readiness. Every automation is documented with an owner, its API dependencies, and a runbook, so any engineer can operate and inherit what you build. ### Must-Have - 5+ years of software engineering, including hands-on experience shipping LLM-based or automation systems to production. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Acargomatic%3A5207803008 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.