AI Architect

Great Dane LLC • Savannah, GA

9d • Onsite

About 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.

Requirements

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

Nice To Haves

• AWS certification a plus.

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 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.

Benefits

• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior