Senior AI Security & Governance Engineer
USFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5–8 years of professional experience in security engineering, AI governance, or related enterprise technology roles.
- Required Skills
- PythonProblem SolvingAnalytical thinkingServiceNow
Requirements
- 5–8 years of professional experience in security engineering, AI governance, or related enterprise technology roles.
- Strong hands-on expertise in Python scripting and automation, with experience developing secure validation and enforcement mechanisms.
- Proven experience working with policy-as-code frameworks, rule engines, governance systems, or automated compliance tooling.
- Solid understanding of AI security risks including prompt injection, hallucinations, misuse prevention, runtime controls, and data protection challenges.
- Familiarity with AI governance standards, responsible AI frameworks, and enterprise compliance best practices.
- Experience with enterprise platforms such as Saviynt, ServiceNow, IAM tools, or workflow approval systems is considered an advantage.
- Strong analytical thinking, problem-solving skills, and the ability to work independently in fast-paced remote environments.
- Bachelor’s degree in Computer Science, Information Technology, or a related field preferred.
Responsibilities
- Design and implement runtime AI protection mechanisms including prompt filtering, output validation, abuse prevention controls, and secure operational guardrails for enterprise AI systems.
- Build governance-by-design frameworks through automation, policy-driven enforcement, and scalable monitoring solutions that improve traceability, auditability, and compliance.
- Develop reusable AI safety standards and governance patterns that can be applied consistently across AI agents, workflows, and LLM-enabled platforms.
- Identify, assess, and mitigate AI-related risks such as hallucinations, prompt injection attacks, data leakage, and misuse scenarios in production environments.
- Collaborate cross-functionally with engineering, security, and governance stakeholders to deploy enterprise-grade AI safeguards and secure deployment processes.
- Support the creation of scalable governance architectures that balance innovation enablement with operational security and enterprise compliance requirements.
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