Artificial Intelligence Jobs in Irvine, CA

Design, build, test, deploy, and support internal AI-enabled web applications, APIs, dashboards, and workflow automations. Lead QA automation, integrate systems, establish engineering and deployment standards, and collaborate with stakeholders to improve operational efficiency and govern responsible AI use.

Lead development and execution of enterprise AI strategy, governance, architecture, and adoption. Coordinate cross-functional teams to identify use cases, enable responsible AI, support implementations, measure business value, and drive enterprise-wide AI literacy and standards.

Lead and maintain the integrated delivery plan for data migration and conversion. Coordinate source teams, data engineers, testing, and integrator activities. Track conversion cycles, defects, reconciliations, and sign-offs. Facilitate readiness reviews, support SIT/UAT/cutover, and produce concise status reporting. Use AI tools to summarize, detect mapping conflicts, generate status narratives, and develop repeatable AI-assisted PMO workflows.

Lead IT-side program management for an Oracle ERP transformation: own integrated plans, governance, RAID/dependency management, readiness reviews, and vendor coordination. Use AI tools to synthesize status, detect risks/dependencies, automate PMO workflows, and enable responsible AI adoption across delivery.

Lead GenAI strategy and research to develop scalable LLM and agentic AI applications (e.g., conversational assistants). Analyze data to personalize investment outcomes, collaborate with engineers, productionize models, ensure best practices in data management and evaluation, publish research, and mentor applied scientists.

Lead design and delivery of enterprise-scale AI/GenAI platforms and Databricks architectures across major cloud providers. Drive technical strategy, client discovery, reference architectures (data pipelines, feature stores, model training, vector DBs, real-time inference), mentor teams, define responsible-AI and security best practices, and represent the firm externally.

Develop, validate, and improve machine learning models (regression, classification, forecasting, optimization). Prepare data, perform feature engineering, train and evaluate models, and support deployment with Data/ML Engineering. Communicate results, document methods, and collaborate on experiments and cross-functional initiatives.

Own product marketing strategy and execution for AI laptops/desktops/workstations. Develop positioning, messaging, launch and go-to-market plans; translate technical AI/NPU capabilities into customer value; create sales and communications assets; coordinate regional localization; track product performance; support PR, events, and cross-functional stakeholders throughout the product lifecycle.

Design, build, and operate AWS-native AI/ML systems: RAG pipelines, fine-tuned LLMs, and microservices. Implement IaC (Terraform), CI/CD, policy guardrails, and production deployments integrating Bedrock/SageMaker, LangChain, and telemetry for secure, scalable enterprise use.