Senior Security Engineer (Artificial Intelligence)

Oscar Health; New York (NY); On-site; USD 180,000 - 230,000; Full time

Job summary

Oscar Health is seeking a Senior AI Security Engineer to safeguard our AI-driven services, including data, models, and deployment pipelines. You’ll lead secure-by-default guardrails, design robust risk controls, and collaborate with Data, Engineering, Privacy, HR, and Compliance to keep our AI innovations safe.

The role emphasizes threat modeling, automated controls, and clear metrics reporting for executives, legal, and compliance stakeholders, while promoting a security-first culture.

Qualifications

• 4+ years in technical security engineering, with focus on data or AI frameworks.
• Familiarity with health data regulations (HIPAA) and automated data usage.
• Ability to review and manage code across multiple repositories and teams.
• Experience communicating AI risk to technical and non-technical stakeholders.

Responsibilities

• Lead development and implementation of a comprehensive AI security framework.
• Design, deploy, and operate automated guardrails for safe AI usage.
• Conduct threat modeling and map adversarial tactics against industry frameworks.
• Develop metrics and reporting for executives and compliance teams.
• Promote secure-by-default blueprints and security-first culture across teams.
• Perform other duties as assigned.

Skills

Security engineering

Application security

Cloud security

AI frameworks

Threat modeling

Risk communication

Education

Bachelor’s degree in Computer Science, Data Science, Cybersecurity, or equivalent

Tools

AWS

GCP

IAM

Job description

• As Senior AI Security Engineer, you’ll be at the forefront of safeguarding our digital ecosystem and shaping the secure deployment of artificial intelligence at Oscar
• You will collaborate with dynamic teams across Data, Engineering, Privacy, HR, and Compliance to architect cutting-edge security solutions and proactive guardrails that drive safe AI innovation, secure enterprise model adoption, and protect our business from emerging adversarial threats
• You will report into the Director of Security Engineering
• Spearhead a More Secure AI Data & Model Lifecycle: Lead the development and implementation of a comprehensive AI security framework encompassing secure model adoption, training data pipelines, retrieval-augmented generation (RAG) architectures, and fine-tuning environments to ensure robust safety and compliance
• Design and Implement Safer Guardrails & Contextual Access: Architect, deploy, and operationalize automated controls to mitigate risks such as prompt injection, model poisoning, data exfiltration, and insecure output handling while enforcing least-privilege principles across LLMs and agentic workflows
• Drive Strategic AI Security Initiatives & Threat Modeling: Lead proactive AI red-teaming exercises and map adversarial tactics against industry frameworks like MITRE ATLAS and the OWASP Top 10 for LLMs to continuously harden systems against modern vulnerabilities
• Measure and Report on AI Security Initiatives: Develop innovative metrics and reporting frameworks to evaluate the impact and organizational adoption of AI safety policies, providing clear, actionable insights for executives and ensuring strict accountability to compliance and legal stakeholders
• Champion AI Security Best Practices and Culture: Partner cross-functionally with application and data engineering teams to establish secure-by-default blueprints, helping employees responsibly harness AI technologies while establishing a strong security-first mindset
• Other duties as assigned

4+ years of relevant experience in technical security engineering, application security, cloud security infrastructure, or software engineering with a distinct focus on data security or AI frameworksBachelor’s degree in a technical discipline (Computer Science, Data Science, Cybersecurity, or equivalent technical space)Familiarity with health insurance data regulations (e.g., HIPAA) and their intersections with automated data usage and generative model architecturesAbility to commit, review, and manage code independently across multiple enterprise repositoriesComfort and fluency with cutting-edge frontier AI technologies (e.g., Claude Code, Codex) and a strong aptitude for the continuous, rapid adoption of emerging AI engineering toolsExperience communicating technical AI risk requirements and architectural implications clearly to non-technical business partners, legal, and compliance teamsProven experience evaluating LLM security postures, implementing alignment guardrails, and managing cloud security infrastructure (AWS/GCP IAM boundaries)