Enterprise AI Architect-2

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.2. Full Development Experience (FDE) and Engineering ExcellenceDemonstrate 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.3. Secure-by-Design AI PlatformsArchitect 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.4. AI Engineering, DevSecOps, and Delivery AutomationDesign and implement AI Engineering Harnesses supporting build validation, quality gates, security scanning, automated testing, and deployment automation. Establish enterprise DevSecOps frameworks integrating:

Required Skills: Performance Architect

Job Type: Full Time

Job Category: IT

Job Role: Enterprise AI Architect

Location: Eden Prairie, MN (Hybrid)

Job Type: Full time Permanent

Job Description: Must Have Technical/Functional Skills Enterprise AI Architect with Full Development Experience (FDE), possessing deep expertise in architecture, hands-on software engineering, AI-assisted development, Agentic AI frameworks, DevSecOps, platform engineering, cloud-native solutions, and enterprise data platforms. Proven ability to architect, develop, secure, automate, and operationalize large-scale AI and software solutions while driving engineering excellence through GitHub Copilot, Claude Code, Codex, Databricks Genie, Snowflake Cortex, and modern AI-powered software delivery practices.

Enterprise AI & Solution Architecture: 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. Full Development Experience (FDE) and Engineering ExcellenceDemonstrate 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. Secure-by-Design AI PlatformsArchitect 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. AI Engineering, DevSecOps, and Delivery AutomationDesign and implement AI Engineering Harnesses supporting build validation, quality gates, security scanning, automated testing, and deployment automation. Establish enterprise DevSecOps frameworks integrating:

Required Skills: Performance Architect