AI Architect

About the Role We are looking for an AI Architect to join our team in Minnetonka Mills, MN. This role involves leading the architecture, design, and implementation of enterprise-scale AI solutions using modern architectural patterns and cloud-native technologies. Key Responsibilities • Lead the architecture, design, and implementation of enterprise-scale AI solutions using modern architectural patterns, clean architecture principles, domain-driven design (DDD), and cloud-native technologies. • Define enterprise AI reference architectures, engineering standards, development frameworks, and implementation guardrails to ensure scalability, maintainability, security, and operational excellence. • Drive adoption of Agentic AI, AI-powered software engineering, and intelligent automation across the software delivery lifecycle. • Architect solutions with built-in observability, resilience, governance, security, and compliance from inception through production deployment. • Partner with business, engineering, security, and platform teams to align AI capabilities with enterprise technology strategy and business outcomes. • Demonstrate hands-on full-stack development experience spanning frontend, backend, APIs, data platforms, cloud services, and AI-enabled applications. • Lead development teams in implementing modern engineering practices including test-driven development (TDD), CI/CD automation, code quality enforcement, and platform engineering standards. • Define and enforce software engineering best practices with mandatory automated test coverage, code reviews, architecture reviews, and deployment quality controls. • Drive modernization of legacy applications through refactoring, cloud migration, microservices transformation, and AI-assisted development methodologies. • Establish engineering productivity frameworks leveraging AI coding assistants, automated development workflows, and intelligent code generation. • Architect secure AI and software platforms aligned with OWASP standards, Zero Trust principles, and enterprise cybersecurity requirements. • Implement enterprise controls for HIPAA, PHI, PII, GDPR, and regulatory compliance across data, applications, and AI workloads. • Integrate security validation throughout the development lifecycle using SAST, SCA, container scanning, secrets management, and policy-as-code frameworks. • Design auditable AI systems with governance, lineage, traceability, access controls, and compliance monitoring capabilities. Requirements • Experience in enterprise AI & solution architecture • Hands-on full-stack development experience • Knowledge of modern engineering practices • Understanding of security and compliance standards • Experience with cloud-native technologies and AI platforms