Artificial Intelligence Jobs in Santa Ana, CA

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.

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.

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.

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.

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.

Lead design, implementation, optimization, and administration of scalable database systems and AI/ML data infrastructure. Build vector DBs, embedding stores, RAG architectures, ETL pipelines, and integrations with LLM APIs. Provide technical leadership, performance tuning, security, data governance, and support for AI-enabled applications while mentoring junior staff and driving data quality and monitoring.

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.

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.

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.

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.

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.