Enterprise AI Architect: Secure, Scalable Solutions

Great Dane; Savannah (GA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Competitive compensation

Medical benefits

401(k) Plan with employer match

Tuition Reimbursement

Paid holidays and vacation

Job summary

Great Dane is seeking an AI Architect to define and govern enterprise AI architecture, patterns, and security. You will partner with data and application teams to deliver scalable, production-ready AI/ML solutions aligned with enterprise data policies.

The role focuses on MLOps/LLMOps, governance, and building reusable architecture artifacts to guide delivery and long-term maintainability.

Qualifications

• Bachelor's degree in CS, DS, ML, or related field.
• 7+ years in software/data engineering or data science; 3+ years architecting and delivering production AI/ML solutions.
• Experience integrating AI with enterprise data platforms and deploying models at scale.
• Strong ML/generative-AI patterns knowledge and MLOps/LLMOps.

Responsibilities

• Define reference AI/ML and generative AI architectures for workloads.
• Ensure enterprise data is AI-ready through governance and modeling.
• Partner with Data Architect to align ontology and AI consumption.
• Evaluate and integrate AI platforms; provide build-vs-buy guidance.
• Establish responsible AI practices including governance and privacy.
• Design high-value AI use cases and shepherd them to production.
• Define MLOps/LLMOps patterns and embed into pipelines.
• Support stakeholders with technical architecture and mentorship.

Skills

ML patterns

Generative AI

MLOps/LLMOps

Python

SQL

Kafka/Confluent

Iceberg

Data governance

Stakeholder communication

AWS certification

Education

Bachelor's degree in CS/DS/ML

Master's degree preferred

Tools

Kafka/Confluent

Iceberg

Job description

Great Dane is seeking an AI Architect to define and govern enterprise AI architecture, patterns, and security. You will partner with data and application teams to deliver scalable, production-ready AI/ML solutions aligned with enterprise data policies.

The role focuses on MLOps/LLMOps, governance, and building reusable architecture artifacts to guide delivery and long-term maintainability.