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
The AI Security Engineer (GRC) serves as the organization's dedicated subject matter expert at the intersection of artificial intelligence and cybersecurity within a regulated healthcare environment. This role is responsible for evaluating AI vendors and technologies, establishing and enforcing secure AI implementation standards, and providing hands-on guidance to development and engineering teams adopting AI platforms such as Microsoft Copilot Studio, Azure AI Foundry, Snowflake Cortex, Claude Code, and other large language model (LLM)-powered tooling.
Operating within the HIPAA-regulated landscape, this analyst will ensure AI integrations — including Model Context Protocol (MCP) servers, agentic workflows, command-line interfaces (CLIs), APIs, and third-party AI extensions — are architected and deployed in a manner consistent with NIST AI RMF, HITRUST, and organizational security policies. The role acts as a trusted advisor, security gatekeeper, and enabler for responsible AI adoption across the enterprise.
You Will
1. AI Vendor & Technology Evaluation
Snowflake Cortex — data access controls in AI-generated SQL, Snowpark security, role-based privilege enforcement, Cortex function access policies, and query result exposure risks
2. Secure AI Implementation Guidance for Development Teams
Establish CLI security standards for AI-assisted development tools (Claude Code CLI, GitHub Copilot CLI, Azure Developer CLI), including credential hygiene, shell history scrubbing, and token scope minimization
3. AI Risk Management & Compliance
Maintain the organization's AI Risk Register aligned with NIST AI RMF (Govern, Map, Measure, Manage)
4. Security Integration Reviews
5. Training, Awareness & Policy
Develop AI security training curricula for developers, data engineers, clinical staff, and IT personnel
Author and maintain AI security policies including: Acceptable Use of Generative AI, AI Vendor Onboarding Standards, MCP and Agentic System Security Policy, and Sensitive Data Handling in AI Contexts
Your Qualifications
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Bachelor’s degree in Cybersecurity, Computer Science, Information Systems, or a closely related field
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Master’s degree preferred; equivalent professional experience considered
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7+ years of progressive experience in information security, with a minimum of 2 years focused on AI/ML security or applied AI technology evaluation
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Demonstrated hands-on experience with one or more of the following: Copilot Studio, Azure AI Foundry, Claude / Anthropic APIs, OpenAI API, GitHub Copilot, or LLM agentic frameworks (LangChain, AutoGen, Semantic Kernel)
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Experience working in a HIPAA-regulated environment; healthcare industry background strongly preferred
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Proven track record conducting vendor risk assessments and producing executive-level risk documentation
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Deep understanding of LLM attack surface: prompt injection, indirect prompt injection, system prompt extraction, and model manipulation
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Familiarity with AI red-teaming methodologies and tools (Garak, PyRIT, PromptBench)
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Knowledge of OWASP Top 10 for LLM Applications
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Understanding of AI model lifecycle risks: training data poisoning, supply chain risks in model registries (Hugging Face, Azure Model Catalog)
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Ability to audit and secure Model Context Protocol (MCP) server implementations including:
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Reviewing tool definitions and permissions for least-privilege violations
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Validating authentication mechanisms (no hardcoded credentials, proper token scoping)
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Assessing stdio vs. SSE transport security implications
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Identifying SSRF and command injection risks in custom MCP tool implementations
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Experience securing AI CLIs including credential storage, environment variable exposure, and shell integration risks
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Knowledge of agentic permission models — understanding when AI agents should require human-in-the-loop approval
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Ability to evaluate multi-step AI workflow chains for unintended capability escalation
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Microsoft Copilot Studio: Plugin manifest security review, connector authentication, sensitivity label enforcement
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Azure AI Foundry: Managed identity configuration, private endpoints, content filtering policy management, model deployment governance
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Snowflake Cortex: Securing AI-generated SQL and Cortex LLM functions, Snowpark container security, column-level data masking, network policy enforcement, and OAuth integration for service accounts
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Claude Code: System prompt construction, tool-use permission hardening, CLI credential isolation, API key scoping
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GitHub Copilot Enterprise: Telemetry settings, suggestion filtering for secrets, IDE extension trust policies
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Strong grounding in identity and access management — OAuth 2.0, OIDC, SAML, managed identities, workload identity federation
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API security: authentication schemes, rate limiting, input validation, and output sanitization for AI endpoints
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Network security: micro-segmentation, private endpoints, WAF configuration for AI service ingress
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SIEM/SOAR integration for AI audit log ingestion, anomaly detection, and automated response
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Threat modeling methodologies: STRIDE, PASTA, and application of MITRE ATT&CK and ATLAS frameworks
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Thorough understanding of HIPAA Security Rule requirements and how they apply to AI data processing pipelines
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Experience with HITRUST CSF controls relevant to AI and cloud-based processing of ePHI
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Practical knowledge of NIST AI Risk Management Framework (AI RMF) — Govern, Map, Measure, Manage functions
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Familiarity with EU AI Act classifications and their implications for healthcare AI systems (high-risk AI designation)
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Experience reviewing BAAs and DPAs for AI vendor engagements
What's in it for you?
Base Pay Range: $125,400 to $215,975
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.
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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)
