AI Platform Engineer

🕒 il y a 9 jours

🏖️ New Jersey – Distant

🏖️ New Jersey – Remote

💵 $70 000 - $90 000 / an

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🏗️ Ingénieur Plateforme

👻 Score fantôme 0%

Ce que ça veut dire : la probabilité que personne ne recrute vraiment pour cette offre.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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Intelligent Audit

Site WebLinkedInTous les Emplois

201 - 500 employés

Fondée en 1996

📦 Logistique

☁️ SaaS

🤖 Intelligence artificielle

Logistics • SaaS • Artificial Intelligence

Intelligent Audit is a transportation cost-control and logistics software company that automates freight and parcel audit & recovery and provides logistics spend intelligence, real-time visibility, claims management, carrier payments, and contract management. The company offers AI-powered capabilities (Yosi™, DeepDetectAI™, Polly™) for continuous detection of errors, fraud, service misuse, and cost patterns, plus scenario modeling and network/parcel optimization tools. Intelligent Audit positions itself as a B2B provider for shippers and 3PLs and emphasizes a mix of technology, services, and operational expertise ("proven since 1996").

Description

• Build and improve AI agents and automations for Finance, Operations and Customer Support • Prototype AI workflows, test results and use data to demonstrate time savings or improved outcomes • Develop Python applications, APIs and scripts connecting AI tools to internal systems through APIs and MCP servers • Help build and improve AI infrastructure with guidance from the team lead • Test and review AI-generated code and model output while following security, privacy, access-control and data-handling practices • Document workflows, prompts and operating procedures, and share examples for effective AI-tool use • Build and manage multi-agent workflows and agent-assisted coding tasks; check results and escalate questions or risks • Help deploy and run AI services using Docker, Linux and existing CI/CD pipelines • Help set up monitoring and alerts, read logs, investigate failures and implement reviewed fixes • Collaborate with colleagues to understand automation needs, communicate progress, manage competing tasks and improve solutions through feedback

🎯 Exigences

• Working skills in Python and some shell scripting, demonstrated through coursework, internships or personal projects • Hands-on experience using LLMs or AI APIs to build a tool, project or hackathon solution • Understanding of basic software development practices, including testing, Git, documentation and code review • Practical experience managing multi-agent workflows, including agent-assisted coding projects, with the ability to explain how results were checked • Comfort using Linux, Git and the command line • Exposure to Docker, cloud services such as AWS or DigitalOcean, or CI/CD through classes, internships or personal projects • Curiosity about repetitive business tasks and willingness to learn how to turn them into reliable automations • Habit of validating AI output and checking that a solution works before calling it complete • Problem-solving skills, attention to detail and willingness to ask for help and learn from feedback • Clear communication, collaboration and ability to manage multiple tasks with guidance on priorities • Interest in learning AI tooling, deployment practices and reliable operation of production services • Bachelor's degree in Computer Science, Software Engineering, Information Systems or a related field, recently earned or nearing completion • A practical example of an AI or automation project built, tested and available for discussion, including what was learned and how the outcome was verified • Willingness to build, deploy and support AI tools while learning directly from the team lead • Preferred: SQL and basic database experience • Preferred: Exposure to infrastructure-as-code tools such as Ansible • Preferred: Familiarity with agent frameworks, prompt engineering or evaluating model output • Preferred: Internship or project involving DevOps, SRE or platform engineering • Preferred: Experience extending AI agents or automations beyond an initial prototype • No minimum years of professional experience are required

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