AI Solutions Architect

Job Summary #CA-FT Within Enterprise Analytics & Data Services (EADS), the AI Solutions Architect serves as a senior technical leader and subject matter expert for UC Davis Health's most complex and strategically important data science and artificial intelligence initiatives within UC Davis Health's Health Analytics Core (HAC). The position provides end-to-end technical leadership, translating clinical, operational, and research challenges into scalable, production-grade solutions using advanced analytics, machine learning (ML), Natural Language Processing (NLP), generative artificial intelligence (AI), and emerging technologies. The AI Solutions Architect leads and influences AI/ML architecture, technical strategy, and solution evaluation, development, and operationalization across complex health data ecosystems within clinical, operational, and research environments. The position establishes reusable frameworks, infrastructure, engineering practices, and responsible AI standards while advising institutional leaders on emerging technologies, vendor solutions, and strategic investments. As a senior individual contributor, the position maintains hands‑on technical involvement while leading multidisciplinary initiatives, mentoring technical staff, and advancing institutional capabilities in AI/ML engineering, MLOps, model evaluation, governance, and responsible adoption of data science and AI. Apply By Date: October 16, 2026 at 11:59pm. Selection activities may start at any time. Minimum Qualifications - For full consideration, applicants are encouraged to upload license and/or certification if required of the position Epic Caboodle & Cogito certification required within 6 months of employment Master's degree or higher in a data-analytic or quantitative discipline (e.g., Data Science, Computer Science, Statistics, Mathematics, Biomedical/Health Informatics, Engineering, or an equivalent technical field). 8+ years of progressive, applied advanced data analytics solutions, with substantial hands‑on expertise in production software engineering, machine learning, scalable data engineering, and enterprise system design. Proven track record architecting, engineering, and deploying production-grade Large Language Model (LLM) applications. Hands‑on experience designing, implementing, and maintaining automated LLM evaluation harnesses, testbeds, and benchmarking frameworks. Deep technical expertise spanning both traditional statistical machine learning (e.g., tree‑based ensembles, regression) and modern deep learning architectures (e.g., Transformers, sequence models, embeddings). Experience working with multimodal data, such as images and text, to generate actionable insights. Advanced proficiency in Python and SQL, with demonstrable mastery of modern data science and AI ecosystems (e.g., PyTorch/TensorFlow, Hugging Face Transformers, LangChain/LangGraph, LlamaIndex, Scikit‑learn, MLflow, and vector databases). Demonstrated command of modern SDLC best practices, automated CI/CD pipelines, containerization (e.g., Docker), version control systems (e.g., GitLab), and automated testing/monitoring for deployed models and services. Practical expertise in transforming, aggregating, and modeling complex, heterogeneous, and high‑dimensional structured and unstructured data across modern distributed compute and enterprise data platforms. Demonstrated understanding of healthcare operations, clinical workflows, and health data standards, with the ability to translate clinical terminology and care processes into safe, relevant, and actionable AI/ML solutions. Preferred Qualifications 5+ years of specialized experience in healthcare data science or biomedical informatics, with a proven track record of applying advanced statistical modeling, modern machine learning, and production‑grade agentic AI architectures to solve complex clinical, operational, and research challenges. Hands‑on experience architecting and integrating data pipelines with clinical exchange standards and protocols, including HL7 FHIR APIs, USCDI, and medical terminology ontologies coupled with deep proficiency across both relational and non‑relational database management systems. Extensive practical experience architecting and executing solutions across unified analytics and cloud data platforms, electronic health record (EHR) data environments, and enterprise business intelligence frameworks. Practical experience architecting and managing end‑to‑end ML Ops / LLM Ops pipelines, including automated model packaging, CI/CD deployment automation, feature stores, experiment tracking, automated model governance, and telemetry monitoring (e.g., data drift, concept drift, system latency) in regulated environments. Demonstrated success partnering directly with physicians, nurse informaticists, clinical operational leaders, and healthcare executive sponsors to translate unstructured clinical documentation, electronic health record (EHR) workflows, and patient care pathways into actionable, high‑impact AI/ML deliverables. Experience designing and delivering interactive workshops, and educational programs on data science, machine learning, and generative AI methodologies to upskill technical staff, researchers, and clinical stakeholders. Experience representing an organization in institutional, national, or international technical forums, conferences, committees, or research collaborations. Key Responsibilities 50% - Technology Leadership 30% - Advanced Analytics & Artificial Intelligence (AI) Development 20% - Training and Mentoring Department Overview The UC Davis Health Enterprise Analytics & Data Services (EADS) department serves as UC Davis Health's enterprise resource for data, analytics, decision intelligence, custom AI, and health computing, enabling the clinical, operational, research, and academic missions through data‑driven decision‑making. Department Specific Job Scope EADS provides the infrastructure, tools, and expertise needed to transform data into actionable insights while developing and delivering enterprise analytics and AI solutions, dashboards, and decision‑support capabilities that advance strategic initiatives and improve organizational performance. POSITION INFORMATION Salary or Pay Range: $12,390.00-$25,725.00 Salary Frequency: Monthly Salary Grade: 112 UC Job Title: CMPTL & DATA SCI RSH SPEC 5 RP UC Job Code: 005241 Number of Positions: 1 Appointment Type: Staff: Career Percentage of Time: 100 Shift (Work Schedule): M-F Location: UCDHAS Building (HSP165) Union Representation: RP-Research and Public Service Professionals Benefits Eligible: Yes This position is hybrid (mix of on‑site and remote work) Benefits Outstanding benefits and perks are among the many rewards of working for the University of California. UC Davis offers a full range of benefits, resources and programs to help you bring your best self to work, as well as to help you and your family achieve your health, wellness, financial and career goals. Learn more about the benefits below and eligibility by visiting UCnet Benefits Page or Benefits Summary for UC Davis Health Employees or Benefits Summary for UC Davis Employees. High quality and low‑cost medical plans to choose from to fit your family's needs UC pays for dental and vision coverage for you and your family Retirement plans for eligible employees including Pension and other Retirement Saving Plans Supplemental insurance offered including additional life, short/long term disability, pet insurance, legal coverage, accident, critical illness and hospital indemnity Pregnancy and Parental Leave, Family & Medical Leave, Adoption Assistance and Pay for Family Care and Bonding for eligible employees Lactation Support Program and Family Care discounts and resources Employee Well‑being resources and programming to support thriving in all aspects of employee's lives On‑site Employee Assistance Program including access to free mental health services Generous amount of paid Holidays annually as outlined in the UC Policies or Collective Bargaining Agreements Paid Time Off/Vacation/Sick Time as outlined in the UC Policies or Collective Bargaining Agreements Continuing Education (CE) allowance and Staff Education Reimbursement Program for eligible employees Access to free professional development courses and learning opportunities for personal and professional growth Public Service Loan Forgiveness (PSLF) Qualified Employer and Student Loan Debt Counseling Program for eligible employees Physical Demands Standing - Occasional up to 3 Hours Walking - Occasional up to 3 Hours Sitting - Frequent 3 to 6 Hours Lifting/Carrying 0-25 Lbs - Occasional Up to 3 Hours Pushing/Pulling 0-25 Lbs - Occasional Up to 3 Hours Bending/Stooping - Occasional Up to 3 Hours Squatting/Kneeling - Occasional Up to 3 Hours Twisting - Occasional Up to 3 Hours Reaching overhead - Occasional Up to 3 Hours Keyboard use/repetitive motion - Frequent 3 to 6 Hours Mental Demands Sustained attention and concentration - Frequent 3 to 6 Hours Complex problem solving/reasoning - Frequent 3 to 6 Hours Ability to organize & prioritize - Frequent 3 to 6 Hours Communication skills - Frequent 3 to 6 Hours Numerical skills - Frequent 3 to 6 Hours Constant Interaction - Frequent 3 to 6 Hours Customer/Patient Contact - Frequent 3 to 6 Hours Multiple Concurrent Tasks - Frequent 3 to 6 Hours Work Environment UC Davis is a smoke and tobacco free campus effective January 1, 2014. Smoking, the use of smokeless tobacco products, and the use of unregulated nicotine products (e.g., e‑cigarettes) will be strictly prohibited on any UC Davis owned or leased property, indoors and outdoors, including parking lots and residential space. Special Requirements This is a critical position, as defined by UC Policy and local procedures, and as such, employment is contingent upon clearing a criminal background check(s) and may include drug screening, medical evaluation clearance and functional capacity assessment This position is designated as a mandated reporter under CANRA and UC policy, and employment is contingent on compliance with applicable policies, procedures and training requirements Misconduct Disclosure Requirement: As a condition of employment, the final candidate who accepts a conditional offer of employment will be required to disclose if they have been subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct; received notice of any allegations or are currently the subject of any administrative or disciplinary proceedings involving misconduct; have left a position after receiving notice of allegations or while under investigation in an administrative or disciplinary proceeding involving misconduct; or have filed an appeal of a finding of misconduct with a previous employer. A Culture of Opportunity and Belonging At UC Davis, we're committed to solving life's most urgent challenges and building a healthier, more resilient world. We believe in growing through every challenge, continually striving to improve, and welcoming new perspectives that strengthen our community. The best ideas often emerge when people with different experiences come together. As you consider joining UC Davis, we invite you to explore our Principles of Community, our Clinical Strategic Plan and strategic vision for research and education. We believe you belong here. The University of California, Davis is an Equal Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status. 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