Artificial Intelligence Jobs in Irvine, CA

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 end-to-end delivery of a high-visibility real-time technology platform, coordinating business stakeholders and engineering teams. Translate requirements into technical tasks, API specifications, and sprint backlogs; facilitate Agile ceremonies; manage risks, dependencies, milestones, and project health reporting. The role requires strong software delivery, consulting, stakeholder management, SDLC, and Agile expertise, with on-site availability in Irvine two to three days weekly for an estimated six-month engagement.

Develops advanced machine learning, deep learning, signal processing, optimization, and numerical modeling algorithms for biomedical signals and next-generation medical devices. Responsibilities include algorithm design, implementation, testing, documentation, data analysis, disease detection and prediction modeling, patentable innovation, and collaboration with hardware and software engineering teams.

Leads strategic planning, portfolio management, and executive decision support for Advanced Innovation & Technology. Owns Digital and AI strategy, roadmaps, prioritization, value realization, and governance while aligning R&D, clinical, regulatory, technology, finance, and other stakeholders. Develops strategic analyses, executive recommendations, portfolio narratives, and leadership communications for future medical device, digital health, data, and AI-enabled capabilities.

Designs, builds, and operationalizes production AI solutions for automotive applications, including LLM applications, RAG pipelines, intelligent agents, predictive models, and generative AI tools. Develops full-stack, cloud-native systems, prototypes AI capabilities, improves prompts and model performance, and integrates enterprise platforms. Collaborates with engineering, product, and data teams while ensuring governance, privacy, security, reliability, and observability standards.

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 strategy, development, and launch of commercial auto insurance products for emerging mobility models, including rideshare, delivery, fleets, and autonomous vehicles. Owns market vision, identifies coverage and risk opportunities, builds business cases, designs pricing and underwriting concepts, navigates multistate regulation, and develops partnerships with mobility platforms, OEMs, telematics providers, and technology vendors. Drives cross-functional alignment, product performance, AI integration, and innovation in ambiguous markets.

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.

Define GHD’s future-state enterprise architecture and translate business strategy into technology direction, capability roadmaps, investment priorities, and architectural guardrails. Evaluate emerging technologies, AI, data, cloud, integration, and digital capabilities; advise executives on trade-offs and risks; align strategic programs and transformation initiatives; and lead the Enterprise Architecture capability across a complex global organization.

Leads the design, governance, and operation of secure, reusable enterprise AI platforms. Owns AI architecture, gateway and model routing, observability, production reliability, vendor rationalization, FinOps, platform roadmaps, and developer experience. Chairs the AI Center of Excellence and builds delivery pods through shared-capacity agreements with IT. Provides hands-on technical leadership, manages teams, and establishes standards across AI initiatives.

Leads enterprise AI transformation operations, including operating model design, portfolio governance, intake and prioritization, roadmap development, adoption measurement, investment decisions, executive and Board reporting, organizational readiness, and value realization. Partners across technical and business functions to scale AI capabilities, validate benefits, improve accountability, and align investments with strategic priorities.

Leads strategy, requirements, roadmap, lifecycle, commercialization, adoption, and economics for AI-enabled regulated medical products. Defines intended use, claims, change-control plans, and portfolio investments while partnering with clinical, regulatory, quality, commercial, and technical teams. Oversees AI/ML model governance, product-market validation, workflow integration, analytics, evidence generation, and post-market performance for products developed under formal medical-device design controls.

Full-time hybrid summer technology internship at Johnson & Johnson from May 24 through August 13, 2027. Interns contribute to technology projects across software engineering, data engineering, AI and machine learning, cybersecurity, cloud and DevOps, UX, digital health, platform engineering, and connected devices. Responsibilities include building solutions, analyzing data and processes, collaborating with stakeholders, supporting project portfolios, and developing technology capabilities. The program may serve as a feeder into the Technology Leadership Development Program.

Leads enterprise AI transformation strategy by identifying high-value opportunities, diagnosing workflows, defining KPIs, establishing baselines, modeling financial impact, developing business cases, and measuring realized value. Partners with senior leaders, Finance, Technology, Data, HR, and business owners to prioritize investments, challenge assumptions, evaluate pilots, and create executive recommendations. Builds repeatable frameworks and enterprise-level views of AI value, risk, dependencies, and performance.

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.

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.

Develop and execute the U.S. Aesthetics AI strategy, identify AI opportunities, support high-priority pilots, monitor progress, and scale successful initiatives. Apply machine learning, generative AI, and agentic AI expertise while establishing governance, enabling technology, ensuring data readiness, and promoting responsible AI. The role requires cross-functional collaboration, operational excellence, and communication across management levels.

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.

Develop and maintain high-quality technical manuals, guides, specifications, and related documentation. Lead information sessions with subject matter experts, align content with user needs and product requirements, improve existing materials, manage documentation projects, incorporate usability-testing feedback, and coordinate with design teams on visuals and diagrams. Apply documentation tools, industry standards, and best practices to improve clarity, usability, and content quality.

Lead growth strategy and execution for UpToDate Expert AI across awareness, acquisition, activation, and early engagement. Drive cross-functional initiatives with marketing, sales, engineering, and data teams to improve discovery, onboarding, and activation. Define OKRs, measurement frameworks, run experiments, and translate clinician insights into product and go-to-market actions while balancing clinical, privacy, and regulatory constraints.

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.

Supports consulting clients in identifying, prioritizing, and implementing Generative AI solutions. Responsibilities include facilitating workshops, analyzing requirements and processes, supporting proof-of-concepts, exploring data, developing documentation, testing solutions, tracking project plans, translating business needs into technical specifications, and delivering GenAI training. The role emphasizes Microsoft AI technologies, prompt engineering, Agile and SDLC practices, continuous AI learning, and client collaboration.

Develop and maintain full-stack web applications using C#/.NET, ASP.NET, SQL Server, JavaScript, React or Angular, Azure, and microservices. Responsibilities include architecture, requirements analysis, coding, testing, debugging, deployment, production support, technical documentation, and troubleshooting across on-premises and cloud environments. The role also applies LLM coding agents, agentic coding, and prompt engineering while collaborating with business users, analysts, QA teams, and vendors.