Among computer occupations, all other, AI is already used for a large share of the tasks. Measured exposure for computer occupations, all other: 31% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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Great Dane has filed one layoff notice in the last twelve months, covering 164 workers, most recently December 2025. These are public filings with state labor departments, and an open role can sit alongside them. See the filings

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About the job

Overview

THE ROLE

At Great Dane, we rely on makers and we’re calling on them to join our expanding team, the time has never been better to Embrace Your Great and work in an environment with the highest safety standards in the industry.

The Position: The AI Architect defines the technical architecture, standards, and reusable patterns for enterprise AI, machine learning, and generative AI solutions. This role ensures AI solutions are secure, governed, scalable, supportable, and aligned with enterprise data and application architecture. The AI Architect partners with Enterprise Architecture, Data Architecture, Data and AI Governance, and Application Development to translate approved AI opportunities into practical solution designs, implementation guidance, and supporting architecture artifacts.

Responsibilities

WHAT YOU’LL DO

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 closely 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 — defining how ontology concepts ground LLMs, RAG pipelines, and agent reasoning, and feeding 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; define build-vs-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 (e.g., predictive analytics, document/entity extraction, decision support) and partner with Development teams to shepherd 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 ensure initiatives support program priorities and deliver measurable value.

Support Business Analysts in assessing and shaping AI solution opportunities by providing the technical perspective — 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.

Other duties as assigned.

Qualifications

COMPETENCIES:

Transformation and Change Management: The ability to lead and execute initiatives that drive significant organizational change, including cultural, process, and structural transformations. Involves assessing readiness, creating a vision, aligning stakeholders, and applying structured change management frameworks.

Operational Rigor: The disciplined application of structured processes, controls, and performance standards to ensure consistency, quality, and efficiency in operations. Focuses on accountability, compliance, and continuous improvement.

Strategic Capability: The capacity to think critically, anticipate future trends, and develop strategies that position the organization for long-term success while balancing short- and long-term needs.

Cultural Fit: The alignment of personal values, behaviors, and working style with the organization’s mission, vision, and culture. Adapts and thrives within the environment while constructively influencing its evolution.

Ability to Build Sponsorship: The ability to gain the support, advocacy, and active involvement of key stakeholders for initiatives, strategies, or change efforts. Builds trust, demonstrates credibility, and aligns initiatives with stakeholder priorities.

YOUR SKILLS & ABILITIES (REQUIRED QUALIFICATIONS)

Education: Bachelor's degree in Computer Science, Data Science, Machine Learning, or a related field; Master's preferred.

Experience: 7+ years in software/data engineering or data science; 3+ years architecting and delivering production AI/ML or generative AI solutions. Demonstrated experience integrating AI with enterprise data platforms and deploying models at scale.

Skills: Strong grounding in ML and generative-AI patterns (RAG, embeddings, model evaluation), MLOps/LLMOps, and cloud AI services (AWS preferred). Proficiency in Python and SQL; familiarity with streaming and lakehouse architectures (Kafka/Confluent, medallion, Iceberg). Working knowledge of data governance and responsible-AI principles. Excellent stakeholder communication. AWS certification a plus.Travel: Occasional; typically less than 10%.

CAREER PATHWAYS:

Prerequisite Positions: Senior Data Scientist, ML Engineer, or Data/Solutions Architect.

Potential Growth Opportunities: Principal AI Architect, Head of AI/ML, or Enterprise Architect.

PHYSICAL/MENTAL REQUIREMENTS:

Office and plant environment.

Keyboarding, lifting, standing, bending, walking.

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

ABOUT GREAT DANE

With a history dating back to 1900, Great Dane has established itself as a transportation solutions leader of today – delivering innovative products and exceptional services that help our customers and employees succeed. We not only engineer durable and high-quality trailers and truck bodies; we foster relationships that last a lifetime.

WHY WORK FOR US?

Great Dane is a leading manufacturer of dry-freight vans, refrigerated trailers, and flatbeds with 10 manufacturing facilities and 20 service centers throughout the United States. With a legacy like ours comes a dedication to the hard-working individuals that make Great Dane what it is today. Our jobs are waiting to be filled by driven, challenge-focused & enthusiastic people like you.

Our culture is comprised of “Champions” and offers a rewarding workplace rooted in core values of safety, leadership, integrity, quality, and passion. Every employee has opportunities to learn, grow, succeed and be engaged in a collaborative environment.

BENEFITS OVERVIEW

Competitive compensation

Benefits, including but not limited to dental, vision, and medical with employer contributions

Retirement programs, including a Pension Plan and 401(k) Plan with employer match

Tuition Reimbursement

Paid holidays and vacation

And more!

Great Dane is an Equal Opportunity Employer