AI Engineer

Summary

Cargomatic is a rapidly growing company disrupting the trucking industry by transforming the way goods move through a technology platform and digital marketplace. They are seeking a highly hands-on AI Engineer to build agentic AI systems and automation tools that integrate with their ecosystem, delivering immediate business value and working alongside a live TMS and RPA stack.

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 backend 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 frontend interfaces from product prototypes, and partner with full-stack engineering to productionize and scale successful prototypes

Skills

• 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
• Backend 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

Qualifications

Must Haves

• 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
• Backend 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

Benefits

• Competitive compensation
• Medical, dental, and vision benefits
• 401K company match program
• Flexible paid time off (PTO) and paid holidays