Guardrails Engineer
Charlotte, NC (Onsite)
The Guardrails Engineer will build and automate guardrail testing, adversarial testing, policy validation, security checks, and evidence generation for AI agents and LLM-powered solutions. This role is responsible for helping ensure safe, compliant, and controlled deployment of Agentic AI use cases.
Key Responsibilities:
- Develop automated guardrail testing frameworks for LLM-powered applications, agents, tools, and workflows.
- Perform adversarial testing, prompt injection testing, jailbreak testing, red-team-style testing, and policy control validation.
- Validate content safety, data protection, security, responsible AI, and model risk controls.
- Build repeatable evidence packages to support approval gates and governance reviews.
- Collaborate with Product Owners, risk, security, observability, and engineering teams to define control requirements.
- Integrate guardrail tests into platform lifecycle, CI/CD, release readiness, and production enablement processes.
- Document findings, control gaps, remediation recommendations, and readiness evidence.
Required Qualifications:
- 7+ years of engineering, security testing, QA automation, risk technology, AI safety, or platform testing experience.
- 5+ years of strong hands-on Python and test automation experience.
- 5+ years of understanding of LLM risks, prompt injection, jailbreak attempts, content safety, data leakage, and Responsible AI controls.
- 5+ years of experience creating test harnesses, validation processes, and repeatable evidence artifacts.
- Ability to work with engineering, security, risk, compliance, and product stakeholders.
Required Skills / Knowledge:
- Python, adversarial testing, red-team testing, prompt security, responsible AI, guardrails, security testing, test harnesses, and evidence automation.
- Understanding of AI governance, model risk, content policy controls, approval gates, and regulated delivery.
- Ability to automate repeatable quality and safety checks for enterprise AI solutions.
Preferred Qualifications:
- Experience with GenAI security, AI red teaming, model risk controls, or regulated AI delivery.
- Experience with CI/CD, observability, Kubernetes, cloud platforms, and enterprise security frameworks.
- Banking or financial services experience.
Expected Outcomes:
- Automated guardrail and adversarial testing framework.
- Repeatable governance evidence for AI approval gates.
- Improved safety, control validation, and release confidence for agents.