AI Architect

AI Architect (GenAI / AI Platform)

Location: Plano, TX (Permanent remote work accepted from anywhere in US)

Role Overview

Define, design, and guide the implementation of scalable AI and GenAI solutions across enterprise environments. Partner with business stakeholders and engineering, platform, security, and delivery teams to translate business needs into production-ready AI-enabled solutions.

Responsibilities

• Define end-to-end architecture for AI/GenAI solutions (application, data, integration, security, deployment)
• Design scalable AI solution patterns using cloud-native services, APIs, vector databases, and orchestration frameworks
• Lead architecture for AI use cases such as:
  • intelligent automation
  • document understanding
  • knowledge retrieval / RAG
  • copilots
  • predictive analytics
  • code or process intelligence
• Assess use cases and recommend fit-for-purpose AI architectures
• Establish architecture standards, reusable patterns, reference models, and best practices
• Guide teams on:
  • model integration
  • prompt orchestration
  • RAG patterns
  • agentic workflows
  • human-in-the-loop controls (as applicable)
• Ensure alignment with enterprise architecture, security, compliance, governance, and operational support
• Support engineering delivery (implementation guidance, code/design reviews, issue resolution)
• Define non-functional requirements: performance, scalability, resilience, observability, supportability, disaster recovery
• Support AI platform selection and tooling strategy; integrate with DevOps, data, and monitoring ecosystems
• Provide technical leadership through discovery, pilot, implementation, and production rollout
• Produce architecture artifacts (diagrams, integration designs, deployment views, decision logs, technical roadmaps)

Requirements

• 7–8 years overall IT experience
• 3+ years focused on AI/ML, data-driven solutions, or intelligent automation
• Strong solution/application architecture and cloud enterprise platform design experience
• Hands-on experience with AI/ML or GenAI components:
  • LLMs
  • RAG
  • prompt engineering and orchestration
  • vector databases / semantic search
  • knowledge graphs or metadata-driven architectures
  • AI workflow orchestration frameworks
• Experience with Azure, AWS, or GCP
• Strong understanding of APIs, microservices, event-driven integration, and enterprise system connectivity
• Data architecture experience (structured/unstructured data, ingestion pipelines, metadata, data governance)
• AI security, responsible AI, access controls, model governance, and enterprise compliance knowledge
• Ability to communicate architecture to technical and non-technical stakeholders
• Experience supporting delivery teams in Agile or product-based environments

Nice-to-have / Additional Skill Signal

• Minimum 5 years experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar