AI Architect

Title: AI Architect
Location: Atlanta, GA
Duration: Long-Term Contract
Experience: 12+ Years

Job Summary

We are seeking an experienced AI Architect to design and lead the implementation of enterprise-grade Artificial Intelligence and Machine Learning solutions. The ideal candidate will have strong expertise in Generative AI, Large Language Models (LLMs), Machine Learning, cloud platforms, AI architecture, and enterprise application integration.

The AI Architect will work closely with business stakeholders, data scientists, engineers, and technology leadership to define AI strategies, design scalable architectures, and deliver secure, reliable, and production-ready AI solutions.

Key Responsibilities

• Design and develop scalable AI/ML and Generative AI architectures aligned with enterprise business requirements.
• Define AI technology strategies, architecture standards, design patterns, and implementation roadmaps.
• Architect solutions using Generative AI, LLMs, NLP, Machine Learning, Deep Learning, and AI agents.
• Design and implement RAG (Retrieval-Augmented Generation) architectures using enterprise data sources and vector databases.
• Evaluate and select appropriate LLMs, foundation models, AI frameworks, and cloud AI services.
• Develop solutions using platforms such as Azure OpenAI, AWS Bedrock, Amazon SageMaker, Google Vertex AI, or equivalent technologies.
• Design AI/ML pipelines covering data ingestion, model development, deployment, monitoring, and continuous improvement.
• Integrate AI solutions with enterprise applications, APIs, databases, data platforms, and business workflows.
• Establish best practices for prompt engineering, model evaluation, fine-tuning, embeddings, vector search, and LLM orchestration.
• Design secure and responsible AI solutions addressing data privacy, security, governance, compliance, explainability, and responsible AI.
• Develop architecture for AI agents and multi-agent workflows where applicable.
• Collaborate with Data Engineers, ML Engineers, Software Engineers, Cloud Architects, and Product teams.
• Provide technical leadership and guidance throughout the AI solution development lifecycle.
• Evaluate emerging AI technologies and recommend solutions that provide business value.
• Establish monitoring and observability strategies for AI/ML models and Generative AI applications.
• Optimize AI solutions for performance, scalability, reliability, latency, and cost.
• Create architecture diagrams, technical specifications, design documents, and implementation guidelines.

Required Skills

• 12+ years of experience in software architecture, enterprise architecture, data/AI engineering, or related technology roles.
• Strong experience designing and implementing AI/ML solutions in enterprise environments.
• Hands-on experience with Generative AI and Large Language Models (LLMs).
• Strong knowledge of RAG, embeddings, vector databases, prompt engineering, and LLM orchestration.
• Experience with Python and modern AI/ML frameworks.
• Strong understanding of Machine Learning, NLP, Deep Learning, and AI model lifecycle management.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Experience with REST APIs, microservices, event-driven architectures, and enterprise integrations.
• Strong knowledge of databases, data lakes, data warehouses, and modern data platforms.
• Experience with AI/ML deployment, MLOps/LLMOps, CI/CD, monitoring, and model governance.
• Strong understanding of cybersecurity and enterprise data protection requirements.
• Excellent architecture, technical leadership, communication, and problem-solving skills.

Preferred Skills

• Experience with Azure OpenAI, AWS Bedrock, Vertex AI, Amazon SageMaker, or equivalent AI platforms.
• Experience with LangChain, LlamaIndex, Semantic Kernel, or similar LLM frameworks.
• Experience with vector databases such as Pinecone, Azure AI Search, OpenSearch, Weaviate, Milvus, or FAISS.
• Experience with Databricks, Snowflake, Kafka, or other modern data technologies.
• Experience designing AI Agents / Agentic AI solutions.
• Experience with Docker, Kubernetes, Terraform, and cloud-native architectures.
• Familiarity with AI governance, model risk management, responsible AI, and enterprise compliance.
• Experience leading enterprise-scale AI transformation initiatives.