We are seeking an experienced and strategic AI Solutions Architect to lead the design, architecture, and implementation of enterprise AI solutions that drive business transformation and innovation. This role is responsible for translating business objectives into scalable AI architectures, guiding technical teams, and ensuring successful deployment of AI-powered products and platforms.
The ideal candidate has deep expertise in Artificial Intelligence, Machine Learning, Generative AI, cloud architecture, enterprise systems integration, and solution design. They possess a strong understanding of both business and technical requirements and can effectively bridge the gap between executive stakeholders and engineering teams.
To support client engagement, collaboration, and strategic business initiatives, candidates must currently reside in one of the following metropolitan areas in the United States:
Dallas
Houston
Austin
Atlanta
Jacksonville
Miami
Nashville
Charlotte
Phoenix
Candidates residing outside of these locations will not be considered for this position.
Design end-to-end AI and Machine Learning solution architectures aligned with business objectives
Develop scalable, secure, and cost-effective AI platform architectures
Define technical roadmaps and AI implementation strategies
Evaluate and recommend appropriate AI technologies, frameworks, and tools
Create architecture diagrams, solution blueprints, and technical documentation
Ensure solutions meet performance, scalability, security, and compliance requirements
Architect solutions leveraging Large Language Models (LLMs), AI agents, and Generative AI technologies
Design Retrieval-Augmented Generation (RAG) systems and enterprise knowledge platforms
Define prompt engineering, orchestration, and agent-based workflows
Evaluate and integrate AI platforms such as OpenAI, Anthropic, Gemini, Llama, Mistral, and other emerging technologies
Design intelligent automation solutions to improve business operations and productivity
Establish AI governance, monitoring, and optimization strategies
Design AI-native cloud architectures across AWS, Azure, and GCP environments
Develop scalable AI infrastructure for model training, inference, and deployment
Define containerization, orchestration, and deployment strategies using Docker and Kubernetes
Collaborate with DevOps and Infrastructure teams to implement CI/CD and MLOps pipelines
Optimize cloud resource utilization, performance, and cost management
Ensure high availability, resilience, and disaster recovery capabilities
Architect integrations between AI platforms and enterprise applications
Connect AI solutions with CRM, ATS, ERP, HRIS, data warehouses, and business systems
Design API-driven architectures and microservices-based integrations
Support enterprise data strategies and interoperability requirements
Ensure seamless flow of data across systems and applications
Define standards for integration security and governance
Design data architectures that support machine learning and AI workloads
Define data ingestion, transformation, storage, and governance frameworks
Collaborate with Data Engineers and Data Scientists on platform design
Ensure data quality, accessibility, and scalability for AI initiatives
Support implementation of vector databases and semantic search solutions
Establish best practices for AI and data platform operations
Ensure AI solutions adhere to enterprise security standards and policies
Design architectures that support privacy, regulatory, and compliance requirements
Establish responsible AI governance frameworks and controls
Conduct architecture risk assessments and mitigation planning
Define monitoring, auditability, and model governance processes
Support compliance with industry-specific regulations and standards
Partner with executives, business leaders, product teams, and engineering teams
Translate business requirements into scalable technical architectures
Lead architecture reviews, technical workshops, and solution design sessions
Provide guidance and mentorship to engineering and AI teams
Support pre-sales, client presentations, and solution demonstrations when required
Drive AI innovation and enterprise transformation initiatives
Bachelor's degree in Computer Science, Engineering, Information Technology, Artificial Intelligence, or a related field
7+ years of experience in software engineering, solution architecture, cloud architecture, or enterprise technology roles
3+ years of experience designing AI, Machine Learning, or Generative AI solutions
Strong understanding of AI/ML architecture patterns and enterprise system design
Experience with cloud platforms (AWS, Azure, and/or GCP)
Strong knowledge of APIs, microservices, distributed systems, and integration architecture
Experience with AI platforms, LLMs, and Generative AI technologies
Strong communication, presentation, and stakeholder management skills
Ability to translate complex technical concepts into business-focused solutions
Must currently reside in one of the approved locations listed above
Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field
Cloud certifications such as AWS Solutions Architect, Azure Solutions Architect, or Google Cloud Professional Architect
Experience with OpenAI, Anthropic, Gemini, Llama, Mistral, or enterprise AI platforms
Knowledge of LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or AI orchestration frameworks
Experience designing RAG, AI agent, and enterprise search solutions
Familiarity with MLOps, ModelOps, and AI governance frameworks
Experience with vector databases such as Pinecone, Weaviate, Qdrant, Milvus, or Chroma
Experience supporting enterprise digital transformation initiatives
Consulting, client-facing, or pre-sales architecture experience
Experience in highly regulated industries such as healthcare, financial services, insurance, or government
AI solutions successfully designed and implemented
Project delivery success rate
Architecture review approval rate
Stakeholder satisfaction scores
Revenue growth or cost savings driven by AI initiatives
Business process improvements and automation outcomes
Adoption and utilization of AI solutions
Strategic objectives achieved through AI implementations
System uptime and reliability
AI platform performance and scalability metrics
Infrastructure cost optimization
Security and compliance adherence
AI innovation initiatives launched
New technologies evaluated and adopted
Contribution to enterprise AI roadmap
Successful proof-of-concept and pilot project outcomes
Cross-functional project success rate
Technical mentorship and team development contributions
Executive and stakeholder feedback
Effectiveness of architecture governance and standards
Director of AI
Head of Enterprise Architecture
Director of Technology
Chief Technology Officer (CTO)
Chief Information Officer (CIO)
Chief AI Officer (CAIO)
Full-Time
Remote (Candidates must reside in approved locations)
Hybrid opportunities may be available based on business and client requirements
Occasional travel may be required for client meetings, workshops, or strategic planning sessions
Agile and collaborative work environment
Fast-paced and innovation-focused technology environment
Collaboration with executives, business leaders, AI teams, and engineering organizations
Opportunity to lead enterprise-scale AI transformation initiatives
Access to modern AI, cloud, and enterprise technology platforms
Strong emphasis on scalability, security, governance, and measurable business outcomes
Career growth opportunities into Enterprise Architecture, AI Leadership, and Executive Technology roles