Artificial Intelligence Jobs in Irvine, CA

Lead architecture and implementation of production-grade agentic systems integrating LLMs across applications. Drive LLM integration strategy, cognitive automation roadmap, scalable distributed system design, best practices, cross-functional alignment, and mentor engineering talent.

The Pre-Sales Data and AI Architect will design and operationalize enterprise data architectures, collaborating with teams to ensure effective integration of Salesforce D360 into complex ecosystems while driving customer success through innovative data solutions.

Lead Responsible AI security and enterprise GRC: perform AI use-case risk assessments and threat modeling, design scalable controls, shape AI governance and policies, support audits, and partner cross-functionally to operationalize AI and information security risk management.

Quota-carrying sales executive responsible for sourcing, developing, and closing technology consulting engagements focused on AI. Manage full sales cycle from prospecting to proposal and contract negotiation, build and maintain pipeline, collaborate on go-to-market strategies, engage executive-level buyers, and participate in marketing events. Hybrid role with travel (~20-25%).

Lead and mentor AI engineers and data scientists to research, prototype, and productionize scalable AI/ML solutions (NLP, CV, predictive analytics, generative AI). Own MLOps, cloud integrations (Azure, AWS, GCP), ethical AI governance, model monitoring/versioning, and cross-functional deployment to meet business objectives.

Serve as the senior client-facing owner who shapes end-to-end data, technology, and AI solutions from ambiguous problem statements through design, build, and adoption. Lead executive conversations, validate technical approaches, partner with architects and engineers, evaluate AI feasibility, and drive process and ways-of-working improvements while supporting delivery.

Design, develop, and deploy AI-powered agents and RAG solutions. Build agentic workflows, integrate LLMs, create data pipelines and embeddings, implement APIs and microservices, deploy on cloud, and monitor scalable AI applications. Collaborate across product and engineering to deliver production-ready solutions.

Lead firmwide AI enablement by setting strategy and roadmap, designing multi-level training, running an AI champion community, producing adoption analytics, shaping governance, evaluating tools and vendors, and managing stakeholders and a small team to drive responsible AI adoption and measurable business impact.

The AI AppSec Engineer V will secure AI solutions, mentor teams, and ensure the integration of security into AI development lifecycles. Responsibilities include threat modeling, code analysis, and contributing to security policies.

Build and maintain marketing data pipelines, replace spreadsheet workflows with structured databases, automate data cleaning/deduplication and syncing, develop AI-driven reports and dashboards, and collaborate with marketing, AdOps, and engineering to ensure reliable, unified, AI-ready marketing data.

Modernize and maintain Magnus and Goliath platforms across Java, Go, and JavaScript. Build AI-powered features (LLMs, tool-calling), integrate BigQuery, GCP, MySQL and internal APIs, diagnose production issues, write automated tests, and own projects end-to-end from design through deployment and support.

Lead cross-functional teams to deliver business strategy and AI advisory services, driving strategic client relationships and AI adoption.

Research, design, and implement foundation models for machine-generated and graph data; develop distributed training and inference pipelines; collaborate with engineering and product teams to productionize models; evaluate new AI/ML techniques and drive MLOps, monitoring, and model optimization to improve scalability and reliability.

Lead end-to-end design, build, and operation of production generative-AI systems (copilots, RAG, agents). Partner with business stakeholders, implement retrieval pipelines, evaluation harnesses, security/privacy controls, observability, and cost optimization. Codify reusable patterns, runbooks, and ensure compliance and operational excellence for deployed AI solutions.

Early-career role to build, operate, and improve cloud data/analytics platforms (Fabric, Snowflake, Databricks). Support platform operations, CI/CD for analytics assets, onboarding for BI tools (Power BI/Tableau), runbooks, monitoring, incident response, and basic security/governance. Work under senior mentorship and contribute to automation, deployment templates, and performance triage.

Lead architecture, operation, and improvement of cloud data and analytics platforms (Fabric, Snowflake, Databricks). Own CI/CD for data assets, BI delivery (Power BI/Tableau), reliability, monitoring, incident response, security, and governance. Enable teams through standards, runbooks, and onboarding; troubleshoot performance and ensure production stability.

As Agentic AI Architect, you'll design AI agent ecosystems, lead architectural development, mentor engineers, and ensure solutions meet business challenges in various domains.

Lead end-to-end video and photo production for the brand: plan and execute shoots, direct a team of six, develop storyboards and scripts, maintain high visual standards, manage budgets and timelines, and step in hands-on to shoot or solve production problems to deliver polished, on-brand content on schedule.

Lead global product marketing for AI systems and accessories, set positioning and go-to-market strategy, manage a team of product marketing managers, translate technical AI hardware capabilities into customer value, drive launches, partnerships, competitive intelligence, and commercial performance across consumer and professional segments.

Design, build, deploy, and maintain AI-integrated full-stack web applications, chatbots, and dashboards. Collaborate with ML and backend teams to ensure secure, scalable, high-availability production systems and monitor model outputs and training analytics.

Develop and operate Digital Twin infrastructure and AI-assisted systems engineering tools. Build multi-fidelity FMU plant models and FMI co-simulations, deploy LLM-based pipelines (RAG, semantic search) integrated with GitLab CI/CD, and perform hands-on systems engineering, requirements authoring, safety analyses, and model correlation with vehicle and fleet data.

Manage inventory and delivery of boundary systems and interfaces for Oracle Fusion programs. Coordinate impact assessments, track integration and testing milestones, facilitate cross-team dependency reviews, maintain RAID items, prepare leadership reporting, and support post-go-live stabilization. Use AI tools to extract system impacts, generate assessments and reports, and help build an AI-enabled knowledge base for impact management.

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.