O
Oscar Health
Security Engineer
Skills
Google Cloud PlatformData EngineeringData ScienceCybersecurityAIAWSCompliance
1 month ago
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Important information
Salary:
$163,944 – $215,176 / year
Location:
New York, NY, USA
Work mode:
Onsite
Published on:
7 October 2026
What they need
Who you are
- 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 frameworks
- Proven experience evaluating LLM security postures, implementing alignment guardrails, and managing cloud security infrastructure (AWS/GCP IAM boundaries)
- Comfort 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 tools
- Experience communicating technical AI risk requirements and architectural implications clearly to non-technical business partners, legal, and compliance teams
- Ability to commit, review, and manage code independently across multiple enterprise repositories
- Familiarity with health insurance data regulations (e.g., HIPAA) and their intersections with automated data usage and generative model architectures
- Bachelor’s degree in a technical discipline (Computer Science, Data Science, Cybersecurity, or equivalent technical space)
What the job involves
- 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
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