Senior AI DeveloperAnalyst

Senior AI Developer/Analyst

We are seeking a Senior AI Developer/Analyst to lead the design development and implementation of AI solutions within our Managed Transportation business.

This role will focus on applying AI/ML to improve operational efficiency enable real time insights and support decision making for Operations and Sales teams.

As a key contributor you ll bridge AI technologies with transportation workflows driving innovation across load planning carrier selection routing visibility and exception management.

Key Responsibilities:
Design and implement AI based solutions to solve business challenges in Managed Transportation including optimization automation forecasting and anomaly detection.
Build and deploy intelligent systems that enhance real time decision making and oversight across operational workflows.
Collaborate with cross functional teams to identify high impact use cases where AI can drive measurable outcomes.
Develop and integrate AI agents/copilots to assist Sales and Operations teams with insights recommendations and customer support automation.
Work with large scale transactional and operational data typical in transportation systems ensuring high data quality and effective data pipelines.
Contribute to the development and operationalization of AI/ML models ensuring performance scalability and maintainability.
Lead or support MLOps practices including version control continuous integration deployment pipelines and model monitoring.

Required Experience & Qualifications:
Proven experience in the design development and deployment of AI/ML solutions in enterprise or logistics focused environments.
Strong understanding of machine learning lifecycle management including data preparation model development validation deployment and monitoring.
Experience working with large structured and unstructured datasets particularly from operational and transactional systems such as TMS ERP or telematics platforms.
Familiarity with cloud based AI platforms and modern data engineering frameworks.
Knowledge of foundational technologies such as messaging systems distributed storage real time data processing and scalable compute environments.
Exposure to or experience with LLMs (Large Language Models) and SLMs (Small Language Models) including their application in enterprise contexts (e.g. intelligent assistants summarization document classification etc.).
Experience implementing or supporting AI agent frameworks or conversational systems to assist end users in business workflows.
Understanding of MLOps best practices including automation monitoring and governance of AI models in production.