AI Architect

AI Architect
Bridgeton, MO

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.
Key Responsibilities
1. 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.
2. Full Development Experience (FDE) and Engineering Excellence
" 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.
3. Secure-by-Design AI Platforms
" 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.
4. AI Engineering, DevSecOps, and Delivery Automation
" Design and implement AI Engineering Harnesses supporting build validation, quality gates, security scanning, automated
testing, and deployment automation.
" Establish ent erprise DevSecOps frameworks integrating:
" Static Application Security Testing (SAST)
" Software Composition Analysis (SCA)
" Container Security Scanning
" Dependency Management
" Policy Compliance Validation
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Publication-ready Job Description
" Infrastructure-as-Code Governance
" Lead implementation of performance benchmarking frameworks for APIs, AI models, applications, and distributed
platforms.
" Build highly automated CI/CD pipelines enabling secure, reliable, and repeatable software delivery.
5. Agentic AI Development Frameworks
" Design and operationalize multi-agent software engineering ecosystems to accelerate architecture, development, testing,
security review, and governance activities.
" Utilize specialized AI agents including:
" Enterprise Architect Agent
" Solution Architect Agent
" Data Architect Agent
" Backend Engineering Agent
" Test Engineering Agent
" Security Review Agent
" Pull Request Review Agent
" Drive adoption of agent-based development workflows to improve engineering productivity, software quality, and delivery
velocity.
6. AI-Assisted Software Engineering Toolchain
" Extensive hands-on experience using:
" Visual Studio Code with GitHub Copilot
" Claude Code
" OpenAI Codex
" Enterprise AI coding assistants
" Leverage repository-wide reasoning, large-scale codebase analysis, architecture discovery, code modernization, and
AI-assisted implementation patterns.
" Architect AI-powered developer experiences integrating intelligent code review, automated remediation, documentation
generation, and engineering workflow automation.
7. Data & AI Platform Architecture
" Design and implement scalable data and AI platforms leveraging Databricks, Snowflake, cloud-native services, and
modern data architectures.
" Experience with:
" Databricks Lakehouse
" Databricks Genie
" Delta Lake
" ML/AI Pipelines
" Snowflake Cortex/CoCo
" Enterprise Data Governance
" Enable self-service analytics, conversational AI, semantic data access, and enterprise-scale data engineering
capabilities