Senior AI Solutions Architect for Health Analytics (Hybrid)

University of California- Davis Health; Sacramento (CA); Hybrid; USD 138,000 - 287,000; Full time

Benefits offered by this job

Hybrid work

Comprehensive benefits

Professional development opportunities

Job summary

University of California- Davis Health is seeking an AI Solutions Architect to lead and implement advanced data science, AI, and ML initiatives across health analytics environments. This role combines hands-on development with strategic leadership to build scalable, production-grade AI solutions that address clinical, operational, and research challenges.

The position focuses on AI/ML engineering, MLOps, model evaluation, governance, and responsible AI adoption, mentoring staff while guiding

Qualifications

• Epic Caboodle & Cogito certification within 6 months of employment.
• Master's degree or higher in a data-analytic or quantitative discipline.
• 8+ years of progressive, applied data analytics with hands-on production software engineering and ML.
• Proven track record architecting, engineering and deploying production-grade LLM applications.

Responsibilities

• Provide end-to-end technical leadership for AI/ML initiatives.
• Lead AI/ML architecture, strategy, and solution evaluation across health data ecosystems.
• Mentor technical staff and advance organizational capabilities in AI/ML engineering, MLOps, and governance.

Skills

Python

SQL

LLM applications

CI/CD

Docker

GitLab

Education

Master's degree or higher in data analytics

Tools

PyTorch/TensorFlow

Hugging Face Transformers

LangChain/LangGraph

LlamaIndex

MLflow

Vector databases

Job description

University of California- Davis Health is seeking an AI Solutions Architect to lead and implement advanced data science, AI, and ML initiatives across health analytics environments. This role combines hands-on development with strategic leadership to build scalable, production-grade AI solutions that address clinical, operational, and research challenges.

The position focuses on AI/ML engineering, MLOps, model evaluation, governance, and responsible AI adoption, mentoring staff while guiding