Security Engineer (REMOTE)

Role overview A remote Security Engineer position that sits at the intersection of security policy and software development, translating security principles into working code and operational controls. The engineer is embedded directly with development squads to harden applications, databases, and AI systems, while playing a central role in an Agentic AI platform transformation by embedding secure-by-design practices from the start.

Responsibilities - Write code, configure systems, and operationalize security controls across production applications, data stores, and AI-driven services. - Partner with policy and development operations teams to translate security requirements into enforceable technical safeguards. - Design and embed secure-by-design patterns that allow engineering velocity without weakening data protection or compliance posture. - Contribute to an Agentic AI platform initiative by assessing model, prompt, and agent safety risks and building mitigations. - Implement and maintain controls around secrets management, identity, network segmentation, and other defensive layers. - Support secure design for microservices and distributed systems, including ETL pipelines and data warehouse environments.

Requirements - Hands-on experience with AI/ML security, model security, and data governance in production environments. - Working knowledge of LLM security topics, including prompt injection prevention and AI agent safety. - Strong coding background in Python, Go, or a comparable language, ideally with prior software development or engineering experience transitioning into security. - Practical experience implementing secrets management solutions such as HashiCorp Vault or AWS Secrets Manager. - Familiarity with zero trust architecture, microservices security, distributed systems security, and data warehouse or ETL security. - One or more relevant certifications (for example CISSP, CEH, OSCP, CSSLP, or a cloud security credential) and general proficiency with standard office software.

Nice to have - Exposure to healthcare or other regulated data environments where compliance requirements shape engineering choices. - Experience collaborating inside an AI platform or applied ML team during an early-stage product buildout.