Find & Apply For Artificial Intelligence Engineer Jobs in Riverside, California

Overview Job

ID 37325788

Category Information Technology Organization Info Technology Solutions Department Reporting and Analytics Dept Location Remote/Hybrid Salary $130,500 - $256,100 Date Posted 2026-05-19T12:00:00.000Z Application Deadline Open Until Filled Schedule 8AM - 5PM Full/Part Time Full-time(100%) Other Information Qalifies for

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No Position Information The Artificial Intelligence (AI) Engineering Lead will lead Information Technology Solutions' (ITS) artificial intelligence and data science initiatives within the Office of Data & Analytics. The incumbent is a proactive leader who can act as a technical strategist and a hands-on expert. This position will partner with leaders across ITS and the UCR campus to bring high-impact AI and Data Science projects to life. As a key technical leader, the incumbent will be responsible for mentoring a team of AI professionals and serving as an AI technical enabler for ITS' development teams. The position will drive the adoption of AI across UCR by empowering teams to integrate AI capabilities into their work, whether it's embedded within custom applications, reporting, or intelligent agents. This role will involve having a constant pulse on solutioning to embed AI within existing products, processes, and initiatives. This position is classified as predominantly remote with occasional visits to campus as needed. Working hours will be based on Pacific Standard Time (PST). The full salary range for the AI Engineering Lead is $126,700 - $248,700 annually. However, the pay scale for this position is up to $200,000 annually. We base salary offers on a variety of considerations, such as education, licensure and certifications, experience, and other business and organizational needs. Applicants must have current work authorization when accepting a UCR staff position. Currently, UCR is unable to sponsor or take over sponsorship of an employment Visa for staff. As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements. Requirements Education Requirements Bachelor's degree in related area and/or equivalent experience/training. Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field. Experience 8 - 13 years of related experience. Proficiency in programming languages like Python and experience with relevant AI/ML frameworks. Vertex AI experience a plus. Proven hands-on experience with data science and AI models and development projects. Experience with data quality and data governance best practices. Experience in a higher education or public sector environment. Demonstrated experience with product management, including requirements gathering, roadmap development, and stakeholder management. Proven experience translating high-level business needs and user requirements into detailed, actionable technical specifications and user stories for development teams. Minimum Requirements Solid understanding of machine learning models, data science methodologies, and generative AI concepts. Demonstrated ability to work with others from diverse backgrounds. Demonstrated effective communication and interpersonal skills. Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization. Self-motivated and works independently and as part of a team. Demonstrates problem-solving skills. Able to learn effectively and meet deadlines. Strong organizational skills. Expert analytical and design skills, including the ability to abstract information requirements from real-world processes to understand information flows in computer systems. Expert knowledge of data management systems, practices and standards. Familiarity with data quality and governance issues and requirements. Thorough knowledge of relevant rules and regulations. Demonstrated ability to effectively communicate with executive-level management on a regular basis. Ability to represent relevant information in abstract models. Critical thinking skills and attention to detail. Preferred Qualifications Solid understanding of machine learning models, data science methodologies, and generative AI concepts. Demonstrated ability to work with others from diverse backgrounds. Demonstrated effective communication and interpersonal skills. Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization. Self-motivated and works independently and as part of a team. Demonstrates problem-solving skills. Able to learn effectively and meet deadlines. Strong organizational skills. Expert analytical and design skills, including the ability to abstract information requirements from real-world processes to understand information flows in computer systems. Expert knowledge of data management systems, practices and standards. Familiarity with data quality and governance issues and requirements. Thorough knowledge of relevant rules and regulations. Demonstrated ability to effectively communicate with executive-level management on a regular basis. Ability to represent relevant information in abstract models. Critical thinking skills and attention to detail. Additional Information In the Heart of Inland Southern California, UC Riverside is located on nearly 1,200 acres near Box Springs Mountain in Southern California; the park-like campus provides convenient access to the vibrant and growing Inland region. The campus is a living laboratory for the exploration of issues critical to growing communities' air, water, energy, transportation, politics, the arts, history, and culture. UCR gives every student, faculty and staff member the resources to explore, engage, imagine and excel. UC Riverside is recognized as one of the most ethnically diverse research universities in the country boasting several key rankings of which we are extremely proud. UC Riverside is proud to be ranked No. 12 among all U.S. universities, according to Money Magazine's 2020 rankings, and among the top 1 percent of universities worldwide, according to the 2019-20 Center for World University rankings. UC Riverside is the top university in the United States for social mobility. - U.S. News 2020 UCR is a member of the University Innovation Alliance, the leading national coalition of public research universities committed to improving student success for low-income, first-generation, and students of color. Among top-tier universities, UC Riverside ranks No. 2 in financial aid. - Business Insider 2019 Ranked No. 2 in the world for research, UCR's Department of Entomology maintains one of the largest collections of insect specimens the nation. - Center for World University Rankings UCR's distinguished faculty boasts 2 Nobel Laureates, and 13 members of the National Academies of Science and Medicine. The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories under state or federal law. It is the policy of the University of California to undertake affirmative action and anti-discrimination efforts, consistent with its obligations as a Federal and State contractor. For information about our generous employee benefits package, visit: Employee Benefits Overview Job Description Details General Information Job Title

DATA SYS ANL 5

Job Code 000600 Grade 27 Department Head Matthew Gunkel Supervisor Michelle Hardwick Generic Scope Recognized organization-wide expert. Has significant impact and influence on organizational policy and program development. Regularly leads projects of critical importance to the organization; these projects carry substantial consequences of success or failure. May direct programs with organization-wide impact that include formulating strategies and administering policies, processes, and resources. Significant barriers to entry exist at this level. Custom Scope Having wide-ranging experience, applies data/information management concepts and campus/medical center/OP objectives to resolve issues, up to and including the most complex, with campus/medical center/OP-wide, institution-wide and/or multi-institutional impact. Formulates strategies and works on issues, up to and including the most complex, with little or no campus/medical center/OP precedent where analyses of situations, information or data requires an in-depth evaluation of variable factors. Selects methods, techniques and evaluation criteria to obtain results. Internal and external contacts often pertain to campus/medical center/OP plans and objectives. Is considered a subject matter expert at campus/medical center/OP and often recognized as an expert externally in the field or industry. Develops conceptual and logical data models with campus/medical center/OP-wide, institution-wide and/or discipline-wide scope. Department Custom Scope The Artificial Intelligence (AI) Engineering Lead will lead Information Technology Solutions' (ITS) artificial intelligence and data science initiatives within the Office of Data & Analytics. The incumbent is a proactive leader who can act as a technical strategist and a hands-on expert. This position will partner with leaders across ITS and the UCR campus to bring high-impact AI and Data Science projects to life. As a key technical leader, the incumbent will be responsible for mentoring a team of AI professionals and serving as an AI technical enabler for ITS' development teams. The position will drive the adoption of AI across UCR by empowering teams to integrate AI capabilities into their work, whether it's embedded within custom applications, reporting, or intelligent agents. This role will involve having a constant pulse on solutioning to embed AI within existing products, processes, and initiatives. Key Responsibilities Develops enterprise data models at several levels of detail. Develops and maintains enterprise dimensional data structures. Specifies processes for maintenance of dimensions and sets of dimensions.

Technical Leadership & Enablement:

Lead and mentor our AI development team in building robust, scalable data science & AI solutions. Empower our existing development teams to integrate AI capabilities into their custom applications and systems. Direct the development of custom AI agents and applications that solve specific campus needs. Establish and lead MLOps (Machine Learning Operations) practices, focusing on the continuous monitoring, tuning, and management of models in production. This includes developing observability processes to monitor model output for hallucinations, ensure validity and truthfulness, and implement automated pipelines for model retraining based on performance degradation or data drift. 50% Directs, initiates and designs data/information management studies. Prepares recommendations for data/information management and/or resource plans having critical, organization-wide and/or institution-wide impact.

Strategy and Vision:

Along with the Chief Data Officer, maintain a comprehensive AI and data science roadmap, identifying high-impact opportunities across academic and administrative functions. Act as a visionary, engaging with campus leaders and teams to understand their challenges and help them envision what's possible with AI and data. Stay current on the latest advancements in machine learning, data science, and generative AI, evaluating their potential to solve our unique challenges.

Product Management & Execution:

Serve as the primary product manager for AI and data science projects, leading the full lifecycle from ideation to release. Gather requirements, translate them into actionable user stories for the AI development team, and manage project backlogs. Coordinate product releases, manage stakeholder communication, and develop training materials for end-users. 15% Regularly leads, directs, analyzes and prepares recommendations for data management information needs across process domains and academic disciplines. Performs analysis, up to and including the most complex and advanced.

Data and AI Foundation :

Collaborate with data engineering and architecture teams to establish data priorities, ensuring a trusted, high-quality data foundation to fuel our AI efforts. Advise on best practices for data governance, MLOps, and ethical AI development. 15%

People Development and Team Leadership:

Foster a culture of servant leadership within your team, prioritizing the growth and well-being of your direct reports. Empower your team to make decisions, take ownership of their work, and grow their skills. Act as a coach and mentor, helping your team members overcome obstacles and achieve their professional goals. 10% Designs overall sourcing strategies. Designs and maintains communication across functional areas or disciplinary domains.

Communication & Literacy :

Act as a subject matter expert, communicating the value and application of both generative AI and machine learning to diverse, non-technical audiences. Help campus users understand how to use these technologies, sometimes blending both approaches into a single cohesive product. 5%

Agile Leadership:

Mentor the Data Science & AI team in an agile development process, guiding daily stand-ups, sprint planning, and retrospectives along with our scrum master. Manage project backlogs and ensure a steady cadence of product delivery, helping the team prioritize tasks and remove blockers. 5% Special Conditions Must pass a background check. Exercise the utmost discretion in managing sensitive information learned in the course of performing their duties. Sensitive information includes but is not limited to employee and student records, health and patient records, financial data, strategic plans, proprietary information, and any other sensitive or non-public information learned during the course and scope of employment. Understands that sensitive information should be shared on a limited basis and actively takes steps to limit access to sensitive information to individuals who have legitimate business need to know. Ensure that sensitive information is properly safeguarded. Follow all organizational policies and laws on data protection and privacy. This includes secure handling of physical and digital records and proper usage of IT systems to prevent data leaks. The unauthorized or improper disclosure of confidential work-related information obtained from any source on any work-related matter is a violation of these expectations. Occasional travel for university related business meetings, conferences and/or professional development. Travel Outside of Normal Business Hours