Applied AI Security Engineer

SimplePractice•Santa Monica, CA

1d•$115,000 - $145,000

About The Position

At SimplePractice, we are improving access to quality care by equipping health and wellness clinicians with all the tools they need to thrive in private practice. More than 250,000 providers trust SimplePractice to build their business through our industry-leading software with powerful tools that simplify every part of practice management. From admin work to clinical care, our suite of innovative solutions work together to reduce administrative burden—empowering solo and small group practitioners to thrive alongside their clients. Recognized by MedTech Breakthrough as the Best Practice Management Solution Provider in 2024 and the Digital Health Awards in 2023, SimplePractice is proud to pave the future of health tech. The Role SimplePractice is a leading practice management platform for health & wellness professionals. We are dedicated to empowering practitioners to run their businesses more efficiently and securely. We are seeking an Applied AI Security Engineer who will play a pivotal role in safeguarding our platform. In this role, you will be a hands-on builder and implementer, working closely with our innovative product and engineering teams to develop and deploy AI-driven security solutions to protect our client data. You will actively contribute to enabling enhanced security capabilities, mitigating risks, ensuring compliance with healthcare regulations, and advancing our mission of securely empowering health & wellness professionals through reliable AI solutions. You’ve been a hands-on, early adopter of AI technologies and understand the promise and the pitfalls. You’ve applied your knowledge to traditional security functions like cloud security, application security, security operations and are eager to take an AI-first approach. You bring full stack skills that can develop and productionalize AI agents to help us scale our security capabilities.

Requirements

5+ years of experience in information security, with recent focus on AI/ML systems
Proven hands-on experience in designing, developing, and deploying AI/ML security solutions, including expertise in model security, data poisoning prevention, prompt injection guardrails, and privacy-preserving techniques.
Strong background in security architecture and threat modeling
Strong bias towards automating with AI as a partner
Demonstrated experience in implementing AI security controls within a regulated environment, with a strong emphasis on practical application and automation.
Degree in Computer Science, Cybersecurity, or a related field
Experience implementing Nvidia NeMo guardrails, ModelArmor or similar LLM protect frameworks
Demonstrated experience with serverless cloud technologies like Lambda, Cloud Run
Knowledgeable in Amazon Bedrock, OpenAI APIs, Langchain, ADK or similar AI model platforms
Strong software development background with proficiency in python, rust or similar languages, including experience with MLOps and DevSecOps practices and tools such as terraform.
Understanding of healthcare compliance (HIPAA, HITECH)
Excellent analytical, problem-solving, and communication skills
Ability to work independently to learn new technologies, processes, frameworks, and systems.

Nice To Haves

A ‘hands-on’ security certification (SANS, CEH, etc)
Experience in healthcare or medical device security
Familiarity with AI ethics and responsible AI development practices
Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes)
Experience contributing to open-source AI security projects or developing internal AI security tools/frameworks.
Familiarity with security automation and orchestration platforms (e.g., SOAR) and how AI can augment or replace these tools.

Responsibilities

Applied AI Security Engineering: Design, build, and implement secure AI solutions to automate our security function, serving as a hands-on expert in secure AI implementation patterns. Enable our security team to move from AI as assistant to AI as automated enabler
Collaborate with product teams to evaluate security implications of new AI features
Actively develop and contribute code to AI security testing tools, including red team AI agents, to proactively identify and address vulnerabilities in new features and models.
Lead incident response for AI-related security events
Integrate AI capabilities directly into security operations workflows to automate threat detection, incident response, and vulnerability management.
AI Security Architecture & Strategy: Design and implement security architecture for AI systems, including LLMs and ML platforms
Develop security standards and patterns for AI development and deployment
Threat modeling for AI features
Establish security controls for model training and monitoring
Translate AI security strategies into actionable development plans and prototypes.
Vendor & Technology Assessment: Evaluate AI vendors and SaaS providers for security, compliance and data protection
Assess emerging AI security tools and technologies
Review cloud-based AI services for healthcare compliance
Risk Management & Compliance: Partner with legal and compliance teams ensure AI initiatives meet regulatory and contractual requirements
Implement controls for data privacy, model integrity, and access management
Develop metrics and reporting for AI security posture
Liaison with customers and auditors on SimplePractice’s approach to AI security and compliance
Leverage AI and automation to operationalize security and compliance workflows, continuously monitoring and improving our security posture