- Design, build, and maintain AISEs guardrail library, including reusable prompt sanitization SDKs, output filtering functions, PII/PHI redaction modules, and topic boundary enforcement components.

- Develop and maintain AISEs adversarial test automation framework covering OWASP LLM Top 10 and MITRE ATLAS TTPs, including prompt injection, indirect prompt injection, RAG exfiltration, jailbreak, model extraction, agent abuse, and supply chain attacks.

- Operate AISEs adversarial validation tollgate by running adversarial tests against AI workloads submitted for production review, documenting findings and severity, issuing residual risk statements, and supporting production approval decisions.

- Integrate AI security controls into DevSecOps pipelines by building pipeline stages that enforce prompt validation, dependency scanning, model integrity checks, and AI workload security requirements.

- Engineer reusable AI security capabilities, including IaC security modules, SIEM telemetry, anomaly signatures, detection logic, and implementation-ready recommendations for AI development pipelines.

- Embrace our vibrant culture by striving for excellence, focusing on meaningful outcomes, and collaborating effectively.

- Prioritize quality, stay curious, and commit to continuous learning.

- Take ownership, build relationships, and focus on personal growth to drive business strategy, creating unmatched career opportunities and impactful work.

What you must have to be considered:

- 10+ years of experience in security engineering or application security, including 3+ years directly in AI/ML security, red team, or AI security tool development.

- Hands-on development experience with the ability to write and ship production Python, with TypeScript or Go experience preferred.

- Direct experience integrating or extending at least two AI security tools such as Garak, PyRIT, LLM Guard, Presidio, NeMo Guardrails, Lakera Guard, or equivalent tools.

- Practical experience executing prompt injection, indirect prompt injection, and jailbreak attacks against real LLM applications in red team, research, or CTF environments.

- Experience with RAG pipeline security, including retrieval-based data exfiltration, embedding inversion, vector store poisoning, and related defense patterns.

- Experience with agentic system adversarial testing, including agent loop hijacking, tool abuse, and privilege escalation in multi-agent orchestration frameworks.

- Solid understanding of OWASP LLM Top 10 and MITRE ATLAS, with the ability to map TTPs to concrete adversarial test cases.

- Experience integrating security into CI/CD pipelines such as GitHub Actions, Azure DevOps, or Jenkins by building security pipeline stages.

- A strong sense of ownership, desire to create meaningful outcomes, and passion for work that serves a greater good for customers, communities, or global challenges.