Gen AI Architect

About the Role

We are seeking a Generative AI Architect to lead the design and delivery of secure, scalable, enterprise-grade AI solutions. The ideal candidate will define GenAI architecture standards, guide engineering teams, and help transform business opportunities into production-ready applications using large language models, retrieval-augmented generation, AI agents, and cloud technologies.

Responsibilities

• Define the organization’s GenAI architecture, strategy, and technical roadmap.
• Design and oversee scalable solutions using LLMs, RAG, vector databases, AI agents, and multimodal AI.
• Evaluate models, platforms, frameworks, and build-versus-buy options.
• Establish standards for prompt engineering, model evaluation, orchestration, and LLMOps.
• Design cloud-native AI platforms, APIs, data pipelines, and integration patterns.
• Ensure solutions meet requirements for security, privacy, governance, performance, and cost.
• Implement safeguards against hallucinations, prompt injection, data leakage, and unauthorized access.
• Lead architecture reviews, proof-of-concepts, and production deployments.
• Partner with product, data, engineering, security, and business stakeholders.
• Mentor technical teams and communicate complex AI concepts to senior leaders.

Requirements

• Bachelor’s or master’s degree in computer science, AI, Data Science, Engineering, or a related field.
• Experience in software architecture, engineering, machine learning, or data engineering.
• Hands-on experience designing or delivering GenAI or LLM solutions.
• Very strong knowledge of LLMs, embeddings, prompt engineering, RAG, vector search, and model evaluation.
• Proficiency in Python, Java, JavaScript, TypeScript, or a similar language.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with APIs, microservices, containers, Kubernetes, CI/CD, and distributed systems.
• Understanding of AI security, data privacy, responsible AI, and governance.
• Excellent communication, leadership, and problem-solving skills.

Skills

• Experience with Azure OpenAI, Amazon Bedrock, Google Vertex AI, OpenAI, Anthropic, Gemini, or open-source models.
• Familiarity with LangChain, LlamaIndex, Semantic Kernel, MLflow, Databricks, or similar tools.
• Experience with AI agents, fine-tuning, knowledge graphs, or multimodal applications.
• Cloud, AI, machine learning, or data engineering certifications.
• Experience in a regulated industry.

Schedule

Hybrid role requiring onsite presence from day one, with 3 days per week in the office (Charlotte, NC).