Remote AI Engineer — Agentic Automation for Logistics

Cargomatic

United States

On-site

USD 150,000 - 210,000

Full time

14 days+

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Benefits offered by this job

Competitive compensation

Medical, dental, and vision benefits

401(k) company match program

Flexible PTO and holidays

Job summary

Cargomatic, the #1 technology platform for powering local trucking, is seeking an AI Engineer focused on agentic automation. You will prototype and deploy AI-driven, production-ready services that integrate with our TMS and ERP stack, turning ideas into scalable solutions.

Responsibilities include designing agentic AI workflows, API integration, data pipelines with Firestore and Redshift, and building robust guardrails and audit trails while collaborating with product, ops, and full-stack teams.

Qualifications

3+ years in software engineering with hands-on experience shipping AI or automation systems in production enterprise environments.
Strong grasp of agentic AI concepts — tool use, function calling, exception routing, and confidence handling at scale.
Clear understanding of where LLMs and agentic systems outperform RPA — and where they don’t.
Comfortable working alongside RPA developers — understands how to hand off structured outputs into downstream deterministic workflows.
Experience with LLM APIs (Claude, OpenAI) including prompt design, orchestration, and evaluation.
Workflow orchestration experience — n8n, LangChain, Temporal, or similar.
Familiarity with no-code/low-code automation tools including Zapier, with the ability to know when to move beyond them.
Experience building rules-based automation with structured inputs, exception handling, and audit trails.
Familiarity with RAG and vector databases.
Experience integrating with TMS or ERP platforms, including calling core platform/internal APIs to execute production actions.
Back-end proficiency in Node.js; comfort with React for building lightweight interfaces; comfortable partnering with full-stack and data engineering teams to ship into production systems.
AWS experience (Lambda, ECS, S3)
Familiarity with databases and data warehouses such as MongoDB, RDS (PostgreSQL/MySQL), Firestore, and Redshift
Experience integrating third-party APIs and building microservices
Active GitHub or demonstrated track record of shipping AI systems in production beyond the prototype stage

Responsibilities

Design agentic AI workflows for structured logistics operations, with clear escalation paths to human review or RPA where deterministic handling is required.
Call core platform/internal APIs to integrate automation workflows into our TMS and other internal systems, partnering with front-end and back-end engineering on execution.
Integrate LLMs, APIs, and data pipelines into reliable production services — including data engineering tie-ins with systems like Firestore and Redshift.
Build and implement agentic AI systems capable of autonomous decision-making and task execution.
Own evaluation frameworks — accuracy, latency, cost per call, fallback behavior, and exception handling.
Implement guardrails, monitoring, and audit trails for production AI systems.
Collaborate with Product and Ops to define success metrics before building.
Leverage modern LLM ecosystems, including Claude-based and code-first AI frameworks, to build intelligent agents and workflows.
Stay current with advancements in AI/ML, especially in agent frameworks and automation tooling.
Build lightweight front-end interfaces from product prototypes, and partner with full-stack engineering to productionize and scale successful prototypes