Staff Software Engineer, AI Governance

Job description

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 regarding AI safety. Integration Platform Direction: Contribute to the technical direction of the integration platform by proposing and implementing improvements to architecture, tools, and technologies. Production Reliability: Identify and resolve performance bottlenecks, troubleshoot integration issues, and proactively improve the reliability of integrations in production environments. Healthcare Compliance & Security: Ensure all integration work adheres to healthcare compliance and security standards, including HIPAA, HL7, and FHIR, while collaborating with security teams to protect sensitive data. Cross-Functional Collaboration: Partner closely with Legal, Compliance, Security, Data Privacy, and AI Research teams to translate complex regulatory requirements into concrete, automated technical solutions. Vendor assessment and risk management along with secure LLM integrations. Your Qualifications: Required: Experience: 8+ years of professional software engineering experience, with at least 3+ years specifically focused on production ML systems, MLOps, or AI safety infrastructure. Architecture Decision-Making: Proven track record of designing and implementing end-to-end solutions and making successful architectural decisions in complex, enterprise-scale environments. Programming Mastery: High proficiency in Python and at least one systems language (e.g., Go, Java, C++ ). AI/ML Expertise: Strong understanding of LLM architectures, transformer models, retrieval-augmented generation (RAG), and traditional ML algorithms. Building/assessing enterprise-grade AI proxy layers and tools to automatically detect, redact, or anonymize PHI before data reaches external LLM APIs Familiarity with LLM-specific security vulnerabilities (e.g., OWASP Top 10 for LLMs) Adapting commercial AI models (like OpenAI or Anthropic) into healthcare workflows safely. Preferred: Education: B.S. or M.S. in Computer Science, Data Science, or a related technical field (or equivalent practical experience). What Success Looks Like: In 3 Months: Map out the existing AI/ML deployment pipeline, identify critical governance gaps, and deliver a technical roadmap for automated compliance auditing. In 6 Months: Launch the first version of our centralized AI Governance, enabling product teams to seamlessly integrate model tracking, bias testing, and safety guardrails into their existing CI/CD workflows. In 12 Months: Establish a comprehensive, real-time AI risk-monitoring dashboard that successfully scales to support all enterprise-wide AI systems, ensuring 100% compliance with relevant regulatory standards. What's in it for you? Base salary range: $106,200 to $182,983 annually An annual employee bonus program Robust Wellness Program Generous paid-time-off (PTO) 11 paid holidays per year, 1 floating holiday, birthday off, and 2 volunteer days Excellent 401(k) Retirement Saving Plan with employer match Robust employee recognition program Tuition reimbursement An opportunity to become part of a team that makes a difference to our members and our community every day! We're always looking for talented people to join our team! Qualified applicants are encouraged to apply now! At SCAN we believe that it is our business to improve the state of our world. Each of us has a responsibility to drive Equality in our communities and workplaces. We are committed to creating a workforce that reflects our community through inclusive programs and initiatives such as equal pay, employee resource groups, inclusive benefits, and more. SCAN is proud to be an Equal Employment Opportunity and Affirmative Action workplace. Individuals seeking employment will receive consideration for employment without regard to race, color, national origin, religion, age, sex (including pregnancy, childbirth or related medical conditions), sexual orientation, gender perception or identity, age, marital status, disability, protected veteran status or any other status protected by law. A background check is required. #LI-JB1 #LI-Hybrid Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information. 41 CFR 60-1.35(c)