Artificial Intelligence Jobs in Santa Ana, CA

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.

Lead and grow the Audit & Assurance practice by managing complex audit engagements, mentoring staff, driving process and technology innovation (AI/automation/analytics), expanding cross-selling across service lines, and developing client relationships with entrepreneurially driven businesses toward partnership.

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.

The role involves designing AI systems for IC calibration and optimization, collaborating with design teams, and applying ML techniques to analog/mixed-signal circuits.

Lead a global GTM operations team to redesign, automate, and integrate GTM processes with an AI-first approach. Identify, prioritize, and deploy AI/automation solutions and integrations at scale, collaborate with IT and cross-functional leaders, drive adoption and change management, and serve as a trusted advisor to GTM leadership.

Own the product vision, roadmap, and delivery for AI-enabled platforms across Aprio. Translate practice requirements into user stories, lead development lifecycles, coordinate onshore/offshore teams, validate and integrate LLMs and AI tooling, and engage stakeholders while ensuring responsible AI, data privacy, and client confidentiality.

Partner with attorneys to identify workflow pain points and design, build, and integrate AI solutions and agentic workflows. Implement prompt-engineered applications, integrate with M365/iManage/EDW, iterate with stakeholders, document deliveries, and monitor LLM innovations.

Lead end-to-end delivery of strategic Data & AI programs across product, platform, and internal initiatives. Create and maintain technical schedules, coordinate cross-functional teams and vendors, identify and mitigate data/model/infra risks, validate technical feasibility and scalability, manage stakeholder and executive communications, and drive process improvements while leveraging AI tools to automate PM workflows.

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%).

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.

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.

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.

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.

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.

The Lead Product Engineer will design and deploy enterprise applications, drive Azure migrations, and collaborate with cross-functional teams in an AI-driven environment, mentoring junior engineers and implementing best practices.

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.