AI Architect Jobs in Georgia
AI Architect jobs in Georgia are in strong demand, concentrated in enterprise technology, financial services, healthcare IT, and defense contracting, with openings at every level from associate architect through principal and staff engineer. Atlanta is the dominant hiring hub, with secondary activity in Savannah and Augusta as logistics and military-adjacent tech employers expand. Well-established names such as NCR Voyix, Delta Air Lines, and Equifax maintain large Georgia presences and hire ai architects consistently across cloud AI, data platform, and ML systems specialties. Find a role that fits below and apply directly.
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Role: Generative AI Architect
Location: Atlanta, GA – Onsite
Rate: $80/hr to $85/hr on C2C All Inclusive
Contract job
Job description:
Generative AI Architect to lead the design, architecture, and implementation of enterprise-grade AI solutions leveraging Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), and AI-driven automation platforms. The ideal candidate will have deep expertise in AI architecture, cloud-native platforms, enterprise integration, security, governance, and scalable GenAI application development. The Architect will work closely with business stakeholders, product teams, data engineers, cloud architects, and AI engineers to build innovative AI solutions that enhance customer experience, streamline insurance operations, improve knowledge management, and accelerate decision-making.
Key Responsibilities
AI & Solution Architecture
- Design end-to-end Generative AI solutions using OpenAI, Azure OpenAI, Gemini, Claude, and other enterprise LLM platforms.
- Define reference architectures, design patterns, and best practices for enterprise AI adoption.
- Architect scalable and secure AI platforms supporting conversational AI, knowledge assistants, document intelligence, and intelligent workflow automation.
- Lead architecture reviews and provide technical leadership across AI initiatives.
RAG & Knowledge Systems
- Design and implement Retrieval-Augmented Generation (RAG) architectures.
- Build enterprise knowledge retrieval solutions utilizing vector databases and semantic search technologies.
- Develop grounding strategies to reduce hallucinations and improve response accuracy.
- Integrate structured and unstructured enterprise content into AI solutions.
Agentic AI & Intelligent Automation
- Architect multi-agent systems using LangChain, LangGraph, CrewAI, AutoGen, and similar frameworks.
- Design AI workflow orchestration solutions that enable tool calling, reasoning, planning, and autonomous task execution.
- Develop intelligent automation capabilities supporting underwriting, claims processing, risk assessment, and customer service functions.
Cloud & Platform Engineering
- Design AI solutions on Azure, AWS, and/or GCP.
- Define scalable deployment architectures using Kubernetes, Docker, serverless and microservices patterns.
- Develop secure API-based AI platforms and integration frameworks.
- Collaborate with DevOps and MLOps teams to establish CI/CD pipelines and production deployment strategies.
Governance, Security & Responsible AI
- Implement Responsible AI frameworks and governance controls.
- Establish security guardrails, data protection policies, and compliance standards.
- Design authentication, authorization, secrets management, monitoring, and auditing capabilities.
- Ensure AI solutions comply with enterprise security and regulatory requirements.
Stakeholder Management
- Partner with business leaders to identify AI use cases and innovation opportunities.
- Translate business requirements into technical architecture blueprints.
- Present architecture solutions, roadmaps, and recommendations to executive stakeholders.
- Mentor engineering teams and promote AI adoption across the organization.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science, or related field.
- Around 20 years of software architecture and enterprise solution design experience.
- 5+ years of AI/ML architecture experience.
- Hands-on experience with Generative AI and Large Language Models.
- Strong Python development experience.
- Experience designing enterprise-scale AI platforms and applications.
Required Technical Skills
Generative AI & LLMs
- OpenAI, Azure OpenAI, GPT-4o
- Gemini
- Claude
- Prompt Engineering
- Fine-Tuning
- Model Evaluation
- AI Safety & Governance
RAG & Agentic AI
- LangChain
- LangGraph
- CrewAI
- AutoGen
- RAG Architecture
- Semantic Search
- Knowledge Graphs
- Agent Orchestration
Cloud Platforms
- Microsoft Azure
- AWS
- Google Cloud Platform (GCP)
Data & Search Technologies
- Azure AI Search
- Pinecone
- FAISS
- ChromaDB
- OpenSearch
- Neo4j
- Vector Databases
Development Technologies
- Python
- FastAPI
- REST APIs
- Docker
- Kubernetes
- Terraform
- GitHub Actions
- CI/CD Pipelines
Security & Governance
- OAuth2
- RBAC
- AI Governance
- Responsible AI
- Data Privacy Controls
- Enterprise Compliance Frameworks
Preferred Experience
- Insurance industry experience (Claims, Underwriting, Risk, Policy Administration).
- AI-powered customer service or contact center solutions.
- Enterprise knowledge management implementations.
- Intelligent document processing and OCR solutions.
- Experience delivering GenAI solutions for Fortune 500 organizations.
Expected Deliverables
- Enterprise GenAI reference architecture
- AI platform design and roadmap
- AI governance framework
- Production-ready AI application architecture
- RAG and Agentic AI implementations
- Security and compliance architecture documentation
Role: Generative AI Architect
Location: Atlanta, GA – Onsite
Rate: $80/hr to $85/hr on C2C All Inclusive
Contract job
Job description:
Generative AI Architect to lead the design, architecture, and implementation of enterprise-grade AI solutions leveraging Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), and AI-driven automation platforms. The ideal candidate will have deep expertise in AI architecture, cloud-native platforms, enterprise integration, security, governance, and scalable GenAI application development. The Architect will work closely with business stakeholders, product teams, data engineers, cloud architects, and AI engineers to build innovative AI solutions that enhance customer experience, streamline insurance operations, improve knowledge management, and accelerate decision-making.
Key Responsibilities
AI & Solution Architecture
- Design end-to-end Generative AI solutions using OpenAI, Azure OpenAI, Gemini, Claude, and other enterprise LLM platforms.
- Define reference architectures, design patterns, and best practices for enterprise AI adoption.
- Architect scalable and secure AI platforms supporting conversational AI, knowledge assistants, document intelligence, and intelligent workflow automation.
- Lead architecture reviews and provide technical leadership across AI initiatives.
RAG & Knowledge Systems
- Design and implement Retrieval-Augmented Generation (RAG) architectures.
- Build enterprise knowledge retrieval solutions utilizing vector databases and semantic search technologies.
- Develop grounding strategies to reduce hallucinations and improve response accuracy.
- Integrate structured and unstructured enterprise content into AI solutions.
Agentic AI & Intelligent Automation
- Architect multi-agent systems using LangChain, LangGraph, CrewAI, AutoGen, and similar frameworks.
- Design AI workflow orchestration solutions that enable tool calling, reasoning, planning, and autonomous task execution.
- Develop intelligent automation capabilities supporting underwriting, claims processing, risk assessment, and customer service functions.
Cloud & Platform Engineering
- Design AI solutions on Azure, AWS, and/or GCP.
- Define scalable deployment architectures using Kubernetes, Docker, serverless and microservices patterns.
- Develop secure API-based AI platforms and integration frameworks.
- Collaborate with DevOps and MLOps teams to establish CI/CD pipelines and production deployment strategies.
Governance, Security & Responsible AI
- Implement Responsible AI frameworks and governance controls.
- Establish security guardrails, data protection policies, and compliance standards.
- Design authentication, authorization, secrets management, monitoring, and auditing capabilities.
- Ensure AI solutions comply with enterprise security and regulatory requirements.
Stakeholder Management
- Partner with business leaders to identify AI use cases and innovation opportunities.
- Translate business requirements into technical architecture blueprints.
- Present architecture solutions, roadmaps, and recommendations to executive stakeholders.
- Mentor engineering teams and promote AI adoption across the organization.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science, or related field.
- Around 20 years of software architecture and enterprise solution design experience.
- 5+ years of AI/ML architecture experience.
- Hands-on experience with Generative AI and Large Language Models.
- Strong Python development experience.
- Experience designing enterprise-scale AI platforms and applications.
Required Technical Skills
Generative AI & LLMs
- OpenAI, Azure OpenAI, GPT-4o
- Gemini
- Claude
- Prompt Engineering
- Fine-Tuning
- Model Evaluation
- AI Safety & Governance
RAG & Agentic AI
- LangChain
- LangGraph
- CrewAI
- AutoGen
- RAG Architecture
- Semantic Search
- Knowledge Graphs
- Agent Orchestration
Cloud Platforms
- Microsoft Azure
- AWS
- Google Cloud Platform (GCP)
Data & Search Technologies
- Azure AI Search
- Pinecone
- FAISS
- ChromaDB
- OpenSearch
- Neo4j
- Vector Databases
Development Technologies
- Python
- FastAPI
- REST APIs
- Docker
- Kubernetes
- Terraform
- GitHub Actions
- CI/CD Pipelines
Security & Governance
- OAuth2
- RBAC
- AI Governance
- Responsible AI
- Data Privacy Controls
- Enterprise Compliance Frameworks
Preferred Experience
- Insurance industry experience (Claims, Underwriting, Risk, Policy Administration).
- AI-powered customer service or contact center solutions.
- Enterprise knowledge management implementations.
- Intelligent document processing and OCR solutions.
- Experience delivering GenAI solutions for Fortune 500 organizations.
Expected Deliverables
- Enterprise GenAI reference architecture
- AI platform design and roadmap
- AI governance framework
- Production-ready AI application architecture
- RAG and Agentic AI implementations
- Security and compliance architecture documentation
See All 41 AI Architect Jobs in Georgia
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Find AI Architect JobsAI Architect Jobs by City in Georgia
Where Georgia roles are concentrated, by current openings.
AI Architect Job Market in Georgia
A snapshot from current Georgia openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Consulting & Professional Services
What Georgia Employers Look For
The qualifications that appear most often in AI architect jobs across Georgia.
- Bachelor's or master's degree in computer science, machine learning, or a closely related field
- Hands-on experience designing and deploying large-scale AI and ML systems in production environments
- Proficiency in cloud platforms such as AWS, Google Cloud, or Azure with AI and MLOps tooling
- Experience with LLM integration, generative AI frameworks, or foundation model fine-tuning pipelines
- Ability to translate complex business requirements into scalable AI architecture blueprints for stakeholders
- Familiarity with enterprise data governance, security compliance, and responsible AI standards
AI Architect Jobs in Georgia: Frequently Asked Questions
How do you become a ai architect in Georgia?
There is no state-issued license required to work as an ai architect in Georgia. The typical path begins with a bachelor's degree in computer science, data science, or software engineering, followed by several years of hands-on ML engineering or data architecture experience. Georgia employers strongly value vendor certifications from AWS, Google Cloud, or Microsoft Azure. Building a portfolio of end-to-end AI system designs and contributing to visible projects accelerates hiring consideration significantly.
How much do AI architects make in Georgia?
AI architects in Georgia earn a median of about $104,610 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $60,920 for the lowest 10% to over $173,060 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire ai architects in Georgia?
Employers hiring ai architects in Georgia right now include Modern Family Law, EY, and Koch, based on current listings on Migrate Mate as of November 2026. Georgia's concentration of financial technology firms, large logistics companies, and defense contractors means demand cuts across several distinct industry verticals rather than a single sector.
Which Georgia cities have the most ai architect jobs?
Atlanta, Alpharetta, and Georgia have the most ai architect openings in Georgia. Atlanta dominates because it is home to the headquarters and major operations centers of large financial, media, and enterprise technology companies that run significant AI programs, while any smaller or suburban markets on the list reflect the distributed campuses and R&D offices those same employers and defense contractors operate outside the city core.
Are there remote ai architect jobs in Georgia?
Yes, and more than most fields. About 76% of ai architect openings tied to Georgia are remote or hybrid as of November 2026, reflecting how much of the work centers on design, modeling, and code review rather than on-site infrastructure. The portions of the role most likely to remain fully remote are system design, stakeholder architecture reviews, and model evaluation, while deployment validation at regulated facilities may require occasional in-person presence.
How can I get hired as a ai architect in Georgia with little or no experience?
The most realistic entry path is moving laterally from a data engineering, ML engineering, or cloud solutions engineer role into an associate or junior architect position. Georgia employers such as large Atlanta-based financial institutions and technology consultancies frequently hire from their own engineering teams for architecture roles. Earning a recognized cloud AI certification and completing a personal or open-source project that demonstrates end-to-end system design gives candidates without a formal architect title a concrete credential to present during interviews.
Where can I find and apply to ai architect jobs in Georgia?
You can find and apply to ai architect jobs in Georgia on Migrate Mate, which lists current Georgia openings updated regularly. Find the roles that match your experience level and target location, then apply directly to each one through the listing.
See All 41 AI Architect Jobs in Georgia
Find roles in Georgia that match your experience and apply in just a few clicks.
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