AI Architect Jobs in Atlanta, GA
AI Architect jobs in Atlanta are concentrated in Midtown, Buckhead, and the Perimeter Center corridor, with strong demand across financial services, healthcare IT, and enterprise technology. Employers hiring right now include EY, Koch, and Infosys. Find a role that fits below and apply directly.
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Showing 5 of 41+ AI Architect jobs
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 Atlanta
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Find AI Architect JobsAI Architect Job Market in Atlanta
Who's Hiring
Top Industries Hiring
- Technology & Software
- Consulting & Professional Services
AI Architect Jobs in Atlanta: Frequently Asked Questions
How do I get a ai architect job in Atlanta?
The strongest path into an ai architect role in Atlanta is through the city's large financial services and healthcare IT sectors, which consistently hire for AI-focused roles at their Midtown and Buckhead offices. Candidates who combine hands-on experience with cloud platforms and a portfolio of production ML or LLM deployments stand out. Networking through Atlanta's active tech meetup scene and connecting directly with hiring managers at fintech and health-tech firms gives a real edge over remote applicants.
Which companies hire ai architects in Atlanta?
Companies currently hiring ai architects in Atlanta include EY, Koch, and Infosys, per current listings on Migrate Mate as of November 2026. Atlanta's hiring mix skews toward large enterprises in financial services, healthcare, and professional services, alongside a growing cluster of AI-focused scale-ups in the Midtown and Old Fourth Ward neighborhoods.
Are there remote ai architect jobs in Atlanta?
Yes, ai architect work is relatively remote-friendly given that most deliverables involve architecture diagrams, model design, and code rather than on-site hardware. About 75% of ai architect openings tied to Atlanta are remote or hybrid as of November 2026, reflecting broader tech hiring norms in the city. The fully remote roles tend to concentrate in cloud-native and SaaS-oriented companies, while large Atlanta-based enterprises in finance and healthcare more often require hybrid attendance at their Midtown or Perimeter Center offices.
How can I get a ai architect job in Atlanta with little or no experience?
The most realistic entry path in Atlanta is through a mid-level machine learning engineer or data engineer role at one of the city's large healthcare or financial services firms, then transitioning into architecture work once you have production system experience. Atlanta employers like large hospital systems and regional banks frequently hire junior AI engineers who grow into architect tracks internally. Building a public portfolio of end-to-end AI projects and earning a cloud certification from AWS or Google strengthens your profile for Atlanta's enterprise-heavy market.
Which industries hire the most ai architects in Atlanta?
The sectors hiring the most ai architects in Atlanta are Technology & Software and Consulting & Professional Services, based on current listings on Migrate Mate as of November 2026. Atlanta's role as a regional hub for financial technology, healthcare systems, and Fortune 500 corporate headquarters drives concentrated demand for AI architects who can design and govern large-scale AI deployments within regulated industries.
See All 41 AI Architect Jobs in Atlanta
Find roles in Atlanta that match your experience and apply in just a few clicks.
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