Principal Solution Architect, Artificial Intelligence and Analytics

Overview

The Embedded Intelligence Principal Solutions Architect will be a key technical leader within our newly formed Capability Development & Support team, focusing on designing and architecting innovative AI and automation  capabilities for business applications that leverage artificial intelligence, intelligent automation, data platforms, analytics and any other technologies which comprise the Embedded Intelligence technology stack.   This position requires a versatile technical professional who can develop architectural frameworks, evaluate emerging technologies, and create scalable proof-of-concepts and design practical solutions to enable embedded intelligence in business solutions. The role involves collaborating with business stakeholders to translate needs into comprehensive technical solutions while ensuring alignment with enterprise standards and integration with existing systems.  This role offers a unique opportunity for technologists who enjoy defining the architectural vision for cutting-edge AI capabilities. You'll have the freedom to explore diverse technologies and approaches while building the foundational frameworks that will power intelligent automation across the organization. The role combines architectural leadership with hands-on technical guidance, allowing you to shape how emerging technologies are deployed throughout the organization. For candidates who thrive on designing innovative systems and translating complex technologies into practical business applications, this role provides exceptional growth potential and the satisfaction of seeing your architectural vision drive organizational transformation. 

Our Flexible Future model offers a healthy mix of working in person and virtually, strengthening key elements of the Chick-fil-A culture by fostering collaboration and community.

Responsibilities

• Design and architect core AI capability frameworks including AI Ops, Model Context Protocol (MCP), Agent2Agent Protocol (A2A), Agent Registry, RAG (Retrieval-Augmented Generation) systems, and intelligent search capabilities 
• Develop comprehensive technical architectures for machine learning, computer vision, digital twin, and embedded intelligence applications with consideration for enterprise integration 
• Evaluate and recommend AI/ML technologies including large language models, computer vision tools, and intelligent automation platforms 
• Establish observability and evaluation frameworks for AI applications, including performance monitoring, quality assessment, and continuous improvement processes 
• Create architectural blueprints that ensure scalability, maintainability, security, and integration with existing enterprise systems 
• Design permissioning and security frameworks for AI applications, including OAuth/Okta integration and row-level security (RLS) implementations
• Create cloud-native, containerized solutions using Kubernetes, CI/CD pipelines, and modern DevOps practices to enable rapid prototyping and scalable deployment  
• Collaborate with business units to understand needs and translate them into technical requirements and capability specifications 
• Work with the R&D leader to align solutions with the broader embedded intelligence ecosystem and technology strategy 
• Partner with Technical Delivery teams to facilitate transition of successful prototypes and frameworks to production environments 
• Document architectural approaches, patterns, and implementation guidelines using tools like C4 diagrams or other architectural modeling techniques 
• Create reusable architectural components and patterns that accelerate future AI capability development 
• Stay current with emerging AI/ML trends including advances in generative AI, computer vision, intelligent automation, and AI-assisted development tools 
• Provide technical mentorship and architectural guidance across the organization 
• Ensure solutions follow appropriate governance standards and best practices for AI ethics and responsible deployment

Minimum Qualifications

• Bachelor's degree or equivalent experience
• 6 years of experience in software engineering, solution architecture, or related technical roles with focus on AI/ML systems
• Strong programming skills in multiple languages (e.g., Python, Go, TypeScript/JavaScript)
• Hands-on experience with DevOps practices including Kubernetes, CI/CD pipelines, containerization, and orchestration technologies
• Experience with cloud platforms (AWS, Azure, GCP) and cloud-native infrastructure patterns
• Experience with AI-assisted development tools and modern development workflows
• Understanding of software architecture principles, microservices, and API design patterns
• Demonstrated experience in solution architecture for AI/ML applications or systems design
• Experience designing and implementing technical solutions across multiple domains
• Significant experience in complex software engineering design and delivery at scale
• Experience with TDD, CI/CD, agile, Kanban, or similar software development practices
• Strong analytical and problem-solving skills with ability to architect complex AI systems
• System thinking and architectural planning capabilities for scalable AI infrastructure
• Clear communication skills with ability to explain complex AI/ML concepts to diverse audiences
• Self-directed with ability to work with minimal supervision in R&D environment
• Collaborative approach with strong teamwork orientation and mentoring capabilities
• Comfort with ambiguity and rapidly changing AI technology landscapeIntellectual curiosity and passion for emerging AI/ML technologies and development tools
• Ability to balance technical exploration with practical implementation and enterprise integration
• Creative thinking and innovative approach to AI capability development
• Experience evaluating AI/ML technology vendors and open-source solutions
• Strong collaboration mindset to gather input from diverse stakeholders for AI strategy development
• Excellent written and verbal communication skills, including technical documentation and team facilitation
• Ability to prioritize multiple competing R&D demands and capability development initiatives
• Demonstrated learning agility for rapidly evolving AI/ML technologies and practices
• Proven ability to positively influence engineering culture around AI development practices
• Ability to lead others by influence

Preferred Qualifications

• Bachelor's degree
• Experience with AI/ML evaluation and monitoring tools (e.g., LangFuse, Arize, or similar observability platforms)
• Experience with architectural diagramming tools (C4 modeling preferred, but general architectural diagramming acceptable)
• Experience with machine learning and computer vision applications
• Background in designing data-intensive applications and digital twin technologies
• Experience implementing end-to-end AI/ML technical solutions
• Previous work in research or innovation teams focused on emerging technologies
• Background in enterprise architecture or systems integration
• Working knowledge of frontend development platforms (React, React Native, iOS, Android)
• Experience prototyping and communicating new AI/automation ideas and products
• AWS Cloud Practitioner, AWS Solutions Architect, or equivalent cloud certifications
• Kubernetes/container orchestration certifications

Minimum Years of Experience

Travel Requirements

Required Level of Education

Preferred Level of Education