Staff Software Engineer, AI Governance

Founded in 1977 as the Senior Care Action Network, SCAN began with a simple but radical idea: that older adults deserve to stay healthy and independent. That belief was championed by a group of community activists we still honor today as the “12 Angry Seniors.” Their mission continues to guide everything we do. Today, SCAN is a nonprofit health organization serving more than 500,000 people across Arizona, California, Nevada, New Mexico, Texas, and Washington, with over $8 billion in annual revenue. With nearly five decades of experience, we have built a distinctive, values-driven platform dedicated to improving care for older adults. Our work spans Medicare Advantage, fully integrated care models, primary care, care for the most medically and socially complex populations, and next-generation care delivery models. Across all of this, we are united by a shared commitment: combining compassion with discipline, innovation with stewardship, and growth with integrity. At SCAN, we believe scale should strengthen, not dilute, our mission. We are building the future of care for older adults, grounded in purpose, accountability, and respect for the people and communities we serve. The Job Serves as the Staff technical engineer and visionary responsible for building the infrastructure, tooling, and frameworks that ensure our Artificial Intelligence and Machine Learning systems are safe, compliant, transparent, and trustworthy. This is a high-impact, cross-functional role. You will bridge the gap between cutting-edge AI engineering, legal compliance, and ethical safety standards. You will design and implement scalable systems to monitor, audit, and govern large language models (LLMs), predictive models, and autonomous agents across the entire enterprise product lifecycle. You Will: Architecture Core Engineering: Design, build, and maintain enterprise-grade AI governance platforms, including automated pipelines for model lineage, bias detection, drift monitoring, and compliance auditing. Agentic Guardrails Orchestration: Design and enforce deterministic guardrails for autonomous AI agents, ensuring agent reasoning loops cannot execute actions that bypass HIPAA controls or data boundaries. Standards Frameworks: Establish engineering standards, best practices, and internal processes for reproducible ML and responsible AI deployment. Technical Leadership: Mentoring mid-level and senior engineers, driving technical roadmaps, and making critical architecture decisions