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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr AI Security Engineer - **Company:** Healthfirst - **Location:** Lake Mary, FL, United States - **Experience:** Expert - **Salary:** $134,600.0 - $194,480.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software System Penetration Testing, Microsoft Azure, Software as a Service, Cloud Computing Security, Cyber Security, Computer Programming, Continuous Integration, Information Leak Prevention, Python (Programming Language), Open Web Application Security, OpenAI, Software Engineering, AI Infrastructure, Privacy Controls, Scripting, Retrieval-Augmented Generation, Large Language Models, Google Vertex AI, Software Security, Generative AI, Infrastructure as Code (IaC), Agentic-AI, Cloudformation, AI Platforms, Information Technology, Cybercrime, Bicep, Model Context Protocol, Terraform, Devsecops, Vulnerability Analysis - **Published:** October 26, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3467235571&tx=FP3128FFP&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * Technical Degree in Computer Science or Cyber Security and/or equivalent work experience * Prior work Cyber Security work experience * Experience in security engineering, vulnerability assessment, threat hunting, and incident response * High School diploma or GED from an accredited institution, * 5+ years of experience in application security, product security, security engineering, cloud security, offensive security, or a related technical security discipline. * Strong understanding of application and API security, authentication, authorization, identity, data protection, and secure software development. * Hands-on experience with security architecture reviews, threat modeling, vulnerability assessment, penetration testing, or security testing. * Working knowledge of modern AI application architectures, including LLMs, model APIs, RAG, vector databases, and AI agents. * Understanding of AI security risks such as prompt injection, data leakage, insecure output handling, excessive agency, and unsafe tool or API access. * Programming or scripting experience, preferably Python. * Experience working with cloud-based applications and services. * Ability to communicate technical security risks and remediation recommendations effectively to engineering teams. * Experience securing production generative AI or LLM applications. * Experience with AI/LLM security testing or red teaming. * Familiarity with agentic AI security, including tool permissions and least-privilege access. * Familiarity with Model Context Protocol (MCP) security considerations. * Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or comparable AI platforms. * Familiarity with OWASP guidance for LLM/GenAI applications, MITRE ATLAS, or NIST AI security guidance. * Experience working with PHI, PII, or other sensitive data in a regulated environment. * Experience integrating security testing into CI/CD or DevSecOps workflows. * Experience with software supply-chain security and SBOM practices, including assessing third-party libraries, dependencies, models, prompts, and other AI application components for security risk. * Experience designing secure tool and API consumption patterns for agentic AI, including authentication, authorization, least privilege, trust boundaries, credential management, and control of agent actions. * Experience reviewing or implementing Infrastructure as Code (IaC) and applying security controls to cloud and AI infrastructure; experience with Terraform, Bicep, CloudFormation, or comparable frameworks preferred. ## Description * Perform security architecture reviews and threat modeling for AI-enabled applications. * Conduct hands-on security testing of LLM, RAG, and agentic AI solutions. * Identify vulnerabilities including prompt injection, sensitive-data exposure, insecure retrieval, excessive permissions, unsafe tool use, and authorization weaknesses. * Assess security risks associated with AI agents, APIs, model integrations, vector databases, and third-party AI services. * Partner with developers and AI engineering teams to design and implement practical security controls. * Develop reusable security patterns and guardrails for common AI architectures. * Build or automate security tests and tools used to evaluate AI applications. * Help protect PHI, PII, credentials, and other sensitive information used by AI systems. * Evaluate emerging AI security threats and translate relevant findings into engineering guidance. * Support the organization's broader application security and secure AI development practices. * Help ensure AI systems handling sensitive healthcare and enterprise information are designed with appropriate security and privacy controls. * Assess how PHI, PII, and other sensitive information moves through prompts, models, APIs, retrieval systems, embeddings, vector stores, logs, agents, and downstream systems. * Partner with privacy, compliance, legal, risk, and AI governance teams to translate requirements into practical technical controls. * Support secure and responsible AI adoption consistent with organizational policies and applicable healthcare and regulatory requirements. * Additional duties as required.