Artificial Intelligence Jobs in Santa Ana, CA

Performs technology-focused internal audits across cloud, AI, IAM, SDLC, vulnerability management, and infrastructure domains. Evaluates control design and operating effectiveness, develops audit documentation, conducts risk-based testing and data analysis, identifies findings, recommends remediation, and validates corrective actions. Partners with global stakeholders and presents audit results, emerging risks, and control enhancements to senior management and governance committees while managing multiple audits.

Leads enterprise cloud infrastructure, data platforms, on-premises systems, AI enablement, and technology operations. Defines roadmaps, architecture standards, governance, and operational processes while managing technical teams and managers. Drives modernization, automation, platform reliability, security, resilience, cost optimization, and business continuity. Partners with executives, business stakeholders, cybersecurity, compliance, and risk teams to align technology investments with organizational goals and improve execution.

Conducts in-depth legal and business research for attorneys and administrative teams, synthesizes findings, advises on research strategies, manages research projects, and evaluates information resources. Develops training curricula, delivers onboarding, monitors legal-industry developments and emerging AI research technologies, maintains newsletters and intranet content, and recommends resource purchases. Requires expert knowledge of legal and business research platforms, strong communication skills, and the ability to manage competing priorities independently and collaboratively.

Leads the bank’s enterprise AI strategy, portfolio, engineering capability, governance, vendor and platform strategy, and workforce adoption. Translates business priorities into production AI initiatives, including generative AI and agentic systems, while ensuring risk controls, security, privacy, auditability, model governance, and measurable value realization. Builds and manages senior AI talent, partners with business and control functions, oversees responsible AI practices, and reports progress, cost, risk, adoption, and outcomes to executive leadership and the Board.

Leads Finance enablement strategy, product adoption, transformation, and user experience across the Global Finance Hub. Partners with product owners and Finance leaders to build scalable capabilities, improve ways of working, support new technologies, and align with enterprise centers of excellence. Oversees product enablement, learning, change management, automation, and AI governance while developing a multidisciplinary team and connecting capability initiatives to measurable business outcomes.

Leads large, complex customer technology programs from scoping through deployment and operational handoff. Serves as the primary executive customer interface, translates business objectives into program plans, coordinates Technical Project Managers and cross-functional teams, manages budgets, risks, dependencies, governance, and contractual commitments, and drives delivery across product, engineering, solutions, and operations. The role also supports enterprise-scale expansion, stakeholder alignment, and continuous improvement of program-management practices.

Leads Finance reporting and analytics capabilities, owning reporting products, BI semantic models, governance standards, roadmap, and backlog. Partners with finance and technology stakeholders to deliver scalable solutions, improve data literacy and adoption, automate processes, and apply AI. The role expands into business performance insights, third-party analytics, planning, and forecasting while developing high-performing teams and influencing senior stakeholders.

Supports FP&A and enterprise analytics by developing scalable Power BI reporting, financial models, dashboards, and automated processes. Analyzes financial and operational datasets to identify trends, risks, and opportunities; improves forecasting, budgeting, and recurring reporting workflows using Excel, Python, SQL, Power Automate, and Microsoft platforms. Collaborates with finance, data engineering, IT, and business stakeholders, trains users, maintains governance standards, and contributes to the Pigment planning platform. Evaluates AI-enabled tools to improve reporting efficiency, data quality, and decision-making.

Leads a hands-on engineering team delivering governed data products and AI capabilities across a modern lakehouse. Responsibilities include setting technical direction, designing data products and AI workflows, embedding LLMs and agents into data engineering, overseeing production platforms, recruiting and coaching engineers, and partnering with enterprise data, architecture, platform, and business stakeholders. The role builds a founding team and operating model for AI-native data product delivery across Capital Group.

Ph.D. interns apply machine learning and AI to semiconductor chip design or enterprise engineering tools. Responsibilities include developing ML models for EDA automation, placement, timing, power, and verification, or deploying LLM, RAG, and agentic systems. Interns will train, evaluate, and deploy models, conduct rigorous experiments, collaborate with engineering and technology stakeholders, assess production performance and safety, and present findings to leadership. The role requires doctoral research in AI, machine learning, computer science, electrical engineering, data science, or a related field.

Designs, develops, tests, and supports ServiceNow automation for ITSM, infrastructure, cloud, endpoint, identity, monitoring, and security operations. Builds workflows, integrations, scripts, catalog automations, and AI-enabled solutions using APIs, IntegrationHub, and MID Server. Integrates ServiceNow with enterprise platforms, improves reliability and operational reporting, maintains CMDB alignment, documents solutions, troubleshoots production issues, and ensures compliance with architecture, security, governance, and release standards.

Supports data engineering, analytics, and machine learning infrastructure projects for software-defined vehicle applications. Responsibilities include building Python and SQL data pipelines, maintaining ELT workflows, validating and transforming data, contributing to ML platform infrastructure, implementing automated data quality tests, supporting CI/CD workflows, collaborating with technical teams, and documenting internship work.

Lead enterprise-wide contract management, negotiating and drafting contracts (NDAs, RFPs, SaaS/cloud and vendor agreements), advising business units on risk allocation, overseeing contract lifecycle and outside counsel, ensuring compliance with privacy, information security, and regulatory requirements, and managing a contracts team and budget.

The VP, Risk Transformation will lead initiatives that modernize risk and operational activities using AI and automation, enhancing decision-making, efficiency, and adherence to regulatory standards.

Own the vision, strategy, roadmap, architecture, and delivery of a shared AI enablement platform and AI seller-assist products. Define reusable AI services, governed data and content capabilities, orchestration, retrieval, guardrails, evaluation, and builder tools. Lead discovery, prioritization, launch readiness, adoption, monitoring, and performance measurement while aligning business, product, engineering, data science, legal, risk, and compliance stakeholders across the organization.

Provide expert legal and business research to attorneys and staff using advanced research tools; advise on research strategy; manage research workflow; develop training, onboarding, newsletters, and intranet content; evaluate and recommend online resources; support continuous learning and Research Services initiatives.

Lead AI infrastructure projects, develop GenAI solutions, drive automation strategy, and collaborate with IT and business teams for implementation.

Build and ship end-to-end user-facing features for a generative AI creative platform, spanning React front-end, Node.js APIs, and integration with Python AI services. Implement asynchronous UIs, typed API contracts, component work, and automated tests while participating in code review and product collaboration.

Lead ownership of AI generation services and provider integrations, ensure billing and tenant security, drive platform reliability, observability, cost attribution, and deployment safeguards. Mentor engineers, set technical standards for Python services, and manage incident response and capacity planning for a production AI platform.

Lead presales for data and AI initiatives: design and present Microsoft Fabric-based data platforms, run discovery and AI workshops, scope proposals, translate technical designs into business value, mentor delivery, and support go-to-market and thought leadership.

As an AI/ML Engineer, you will develop multimodal AI models, focusing on computer vision and agentic capabilities. Responsibilities include data curation, model training, evaluation, and deployment while working with real robotic systems.

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.

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.