Staff Security Engineer

Posted 6 days agoViewed
United StatesFull-TimeHealth Tech
Location:United States, EST, PST
Languages:English
Seniority level:Staff, 8+ years
Experience:8+ years
Skills:
AWSLeadershipPythonArtificial IntelligenceCloud ComputingCybersecurityGCPJavaMachine LearningC#C++AzureGoCI/CDLinuxDevOpsMicroservicesMentoringScalaSoftware Engineering
Requirements:
BS/BTech (or higher) in Computer Science, Information Technology, Cybersecurity or a related field, 10 years security domain experience without degree 8+ years of experience in software or security engineering within Cloud Native environments Experience architecting, developing, and deploying large-scale distributed systems at scale Experience with cloud technologies, e.g., AWS, Azure, GCP Experience building continuous integration and continuous development (CI/CD) pipelines Strong familiarity with server-side web technologies (eg: Java, Python, Scala, C#, C++, Go) 4+ years of experience acting as a trusted technical decision-maker in a team setting, solving for short-term and long-term business value Experience with health-tech systems, like Electronic Health Records, Clinical data, etc. Experience with AI/ML Security, including Gemini, Claude, LightLLM, and AWS Bedrock.
Responsibilities:
Lead the development, implementation, and ongoing maintenance of comprehensive security strategies and solutions. Design and deploy advanced security controls to safeguards networks, systems, and applications. Work across disciplines to shape our security services strategy and execution. Mentor and galvanize new engineers to do their best work. Set and uphold the standard for security processes to support high-quality engineering. Lead AI/ML Security program for building SaaS systems using AI models. Design and implement robust security controls for AI/ML systems, covering model training, inference, and data pipelines. Proactively identify and mitigate diverse threats, including model inversion, data poisoning, adversarial attacks, and prompt injection. Collaborate seamlessly with data scientists, ML engineers, and DevOps teams to embed security throughout the entire AI/ML lifecycle. Conduct thorough threat modeling and risk assessments for AI systems and algorithms. Develop and implement methods to monitor AI systems for anomalous behavior and potential misuse. Secure APIs and endpoints critical for model access and inference.
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