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Great Dane

Builds freight trailers and truck bodies

AI Architect

AI & Machine LearningUpdated on Nov 13
Full-timeSavannah, GA, USANo salary listed

About the Job

Requirements

  • A bachelor's degree in Computer Science, Data Science, Machine Learning, or a related field is required; a master's degree is preferred.
  • Seven or more years of experience in software or data engineering or data science, including three or more years architecting and delivering production AI/ML or generative AI solutions.
  • Demonstrated experience integrating AI with enterprise data platforms and deploying models at scale.
  • Strong grounding in machine-learning and generative-AI patterns, including retrieval-augmented generation, embeddings, and model evaluation.
  • Knowledge of MLOps/LLMOps and cloud AI services; AWS is preferred.
  • Proficiency in Python and SQL.
  • Familiarity with streaming and lakehouse architectures, including Kafka/Confluent, medallion architecture, and Iceberg.
  • Working knowledge of data governance and responsible-AI principles.
  • Excellent stakeholder communication.
  • The role works in an office and plant environment and requires keyboarding, lifting, standing, bending, and walking.

Responsibilities

  • Define the reference architecture for AI/ML and generative-AI workloads, including the Durable Hub, Great Dane's central data and integration hub.
  • Ensure enterprise data is AI-ready, well-governed, well-modeled, and accessible by partnering with the Data Architect and Data Governance Committee.
  • Partner with the Data Architect to ensure the enterprise ontology and semantic models are effective for AI consumption, define how ontology concepts ground LLMs, RAG pipelines, and agent reasoning, and feed gaps or ambiguities back into the ontology while the Data Architect retains ownership of its authoritative definition and governance.
  • Evaluate, select, and integrate AI/ML platforms, frameworks, and services, and define build-versus-buy guidance.
  • Establish responsible-AI practices, including governance, evaluation, monitoring, and controls for accuracy, bias, and data privacy.
  • Design and prototype high-value AI use cases, such as predictive analytics, document/entity extraction, and decision support, and partner with Development teams to move them from proof of concept into production.
  • Define MLOps/LLMOps patterns for model lifecycle, versioning, and observability, and collaborate with Development to embed them into delivery pipelines and engineering practices.
  • Align AI architecture and delivery roadmaps with Intelligence Automation project owners and stakeholders to support program priorities and deliver measurable value.
  • Support Business Analysts in assessing and shaping AI solution opportunities by evaluating feasibility, data readiness, implementation complexity, operational impact, and architectural fit to inform business-value and roadmap decisions.
  • Provide architecture direction, solution-design guidance, and implementation artifacts to Development teams, partnering with engineers to co-design production-ready approaches while preserving Development ownership of engineering execution, integration, deployment, and operational support.
  • Own and maintain the AI architecture documentation framework, including reference architectures, solution-design documents, architecture decision records, technical standards, implementation patterns, integration diagrams, data-flow diagrams, operational support models, and supporting artifacts required to guide delivery, governance, and long-term maintainability of AI solutions.
  • Establish and govern documentation standards for AI solutions, ensuring architecture artifacts, technical designs, decision records, diagrams, and implementation guidance are created, maintained, versioned, and stored in approved enterprise repositories such as SharePoint and Miro.
  • Provide technical mentorship on AI patterns to the data engineering and Development teams.
  • Perform other duties as assigned.

Desired Qualifications

  • AWS is the preferred cloud AI service.
  • An AWS certification is a plus.

About the Company

Great Dane

Builds freight trailers and truck bodies

Great Dane builds trailers and truck bodies for trucking fleets that move dry freight, temperature-sensitive goods, and open-deck loads. Its Everest refrigerated trailers support single or multiple temperature zones, while its dry vans and flatbeds cover other freight needs. Customers order equipment configured for their operations, from trailer specifications to technology integrations. The business sells trailers and truck bodies through its distribution network and supplies aftermarket parts and repair services to keep commercial equipment on the road. Great Dane was founded in 1900 and has its corporate headquarters in Chicago, Illinois, with an additional office in Savannah, Georgia.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Chicago, IL
Founded
1900

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