AI Engineer

Cargomatic is hiring an AI Engineer to automate logistics workflows across pricing, dispatch, documents, billing, and invoicing. The role designs, evaluates, and delivers production AI and automation solutions in partnership with Engineering, Platform, Operations, and the RPA team.

Responsibilities:

• 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

Requirements:

• 5+ years of software engineering, including hands-on experience shipping LLM-based or automation systems to production
• Hands-on experience with LLM APIs (Anthropic, OpenAI) and agentic patterns: tool calling, structured outputs, exception routing, and human-in-the-loop
• Sound judgment on when to use LLMs, deterministic software, or RPA
• Experience building evaluation for non-deterministic systems: golden datasets, LLM-as-judge calibrated against human labels, and regression testing when prompts or models change
• Experience evaluating and integrating third-party AI or automation tools, weighing cost, effort, and risk against building in-house
• Strong backend engineering and REST/GraphQL API integration on AWS (Node.js/TypeScript preferred)
• Clear communication with non-technical stakeholders: you can turn an operational workflow into a system design and explain tradeoffs to leadership
• A track record of shipping working systems beyond demos or prototypes
• Freight or logistics background (TMS, EDI, drayage, or carrier/shipper operations)
• Document AI or OCR experience, including confidence calibration and human review workflows
• Experience with RPA platforms (UiPath preferred) and with modernizing or augmenting existing bots with AI
• Low-code automation (Zapier) and workflow orchestration, with judgment on when a workflow should move to code
• SQL and dbt; experience with Redshift, MongoDB, PostgreSQL, or Firestore
• React for lightweight internal tools
• Active GitHub or open-source work