Location: Tustin, CA
Salary: $140,000.00 USD Annually - $150,000.00 USD Annually
Description:
Enterprise Architect - (AI Focus)
Irvine, CA
Fulltime
Enterprise Architect - AI Focus
Experience Required: 10-16 years overall IT experience; 4-6+ years in AI/ML architecture or advanced analytics platforms; strong enterprise integration experience
The Enterprise Architect (AI Focus) provides architectural leadership to assess AI readiness, define future-state AI architecture, and integrate AI capabilities into the broader enterprise ecosystem.
2. Skills Required
Experience designing enterprise-scale AI/ML architectures and integrating AI services into enterprise applications
Knowledge of LLM/GenAI concepts, RAG patterns, and model selection trade-offs
Understanding of MLOps lifecycle concepts: reproducibility, CI/CD for ML, monitoring, and drift
Knowledge of data pipelines and data readiness for AI (structured/unstructured)
Experience with cloud AI services (AWS/Azure/Google Cloud Platform) and secure integration patterns
Understanding of orchestration/event patterns (queues, triggers, APIs) to embed AI into workflows
Familiarity with responsible AI governance concepts (auditability, policy guardrails)
Awareness of PII/regulated data boundaries and access controls for AI workflows
Ability to define logging/audit and approval gates for AI deployments
Ability to translate AI opportunities into measurable outcomes and architecture roadmaps
Strong documentation and executive communication skills
Responsibilities
Drive discovery and business alignment: identify AI use cases aligned with business goals; assess feasibility (technical, legal, ethical) and define measurable outcomes
Design end-to-end AI architecture patterns including AI integration with enterprise apps, event flows, orchestration, and AI input/output pipelines
Define data readiness and knowledge retrieval patterns (e.g., RAG) where appropriate; guide data boundaries and access controls
Define security, compliance, and auditability controls for AI: authentication, rate limiting, prompt/response logging, and retention strategies
Define model management guardrails: model selection guidance, versioning, evaluation, release governance, and rollback strategies
Establish production AI lifecycle architecture with MLOps principles: automation, monitoring, drift detection, reproducibility, and operational readiness
Partner with enterprise architecture/security teams to ensure AI initiatives integrate cleanly with platform governance
Produce executive-ready AI architecture artifacts: target stat e, integration patterns, governance model, and phased adoption roadmap
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Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: cxjudgpa
- Position Id: 1124312
- Posted 3 hours ago
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