AI Security in Engineering Teaching Expert (B2B, Part-time)

Nebius Academy (powered by TripleTen) partners with forward-thinking companies to help technical teams adopt AI safely and build practical, job-ready skills that drive measurable business impact.

We design hands-on learning experiences that help engineers apply AI tools in real-world workflows while understanding the security risks introduced by agentic systems, tool use, delegated permissions, data access, and AI-powered development environments.

As we continue expanding our AI Security portfolio, we're looking for an experienced Instructor AI Security in Engineering to deliver highly practical workshops for engineering teams. This role combines deep hands-on expertise in AI and agentic security with technical facilitation, helping experienced engineers understand and mitigate risks related to prompt injection, MCP trust boundaries, permissions, AI supply-chain vulnerabilities, secure AI-generated code, and data governance.

Brand:
Nebius Academy

What you will do:

• Deliver hands-on AI Security workshops for experienced engineering teams, combining concise concept explanations with practical labs on real repositories.
• Demonstrate real-world attack scenarios and mitigations involving agentic AI coding tools, including indirect prompt injection, delegated permissions, autonomous command execution, and workspace trust.
• Guide learners through MCP security practices, including trust boundaries, read/write scoping, least-privilege configurations, and re-approval of changed tool definitions.
• Help engineers secure AI-generated code and pull requests using DevSecOps controls such as secret scanning, SAST, SCA, branch protection, CODEOWNERS, and repository-level security instructions.
• Explain and demonstrate AI-specific supply-chain risks, including hallucinated dependencies, poisoned tool descriptions, and compromised MCP servers.
• Facilitate practical discussions around AI data governance, including sensitive data exposure, credentials, proprietary code, model data flows, retention, and content exclusions.
• Review the client's AI tooling configuration and existing security controls ahead of workshops to tailor examples and exercises to their environment.
• Collaborate with the Nebius Academy team and subject-matter experts to refine workshop materials, labs, and security practices based on learner needs and evolving AI security risks.

What we can offer you:

• The opportunity to share your expertise while maintaining your primary job: Deliver high-impact AI Security workshops without leaving your current role.
• Competitive hourly rate of $90–$130 USD for flexible part-time collaboration, with the possibility of a higher rate for exceptional expertise.
• Remote cooperation with a schedule convenient for both you and the team: We can work with experts across different locations and time zones.
• Work with experienced engineering audiences: Help technical professionals understand and mitigate real-world security risks introduced by agentic AI systems.
• Meaningful impact: Contribute to practical AI Security education in an area with rapidly growing demand from enterprise clients.
• Participation in innovative projects: Work on hands-on workshops around agentic AI security, MCP, AI supply-chain risks, secure coding workflows, and related emerging practices.
• Potential for continued collaboration: Strong experts may be invited to contribute to future AI Security workshops, courses, and learning content beyond the initial engagement.

Requirements:

Must have

• Strong hands-on experience in AI Security, with practical understanding of security risks introduced by agentic AI systems and AI-assisted engineering workflows.
• Deep understanding of the agentic AI attack surface, including indirect and persistent prompt injection, delegated authority, blast radius, approval flows, workspace trust, and autonomous command execution.
• Practical knowledge of MCP security and trust boundaries, including read/write scoping, least-privilege configuration, permissions, and tool re-approval.
• Hands-on experience with GitHub Copilot, VS Code, and Python, sufficient to demonstrate realistic attacks and mitigations live.
• Strong understanding of DevSecOps controls for AI-generated code, including secret scanning, SAST, SCA, branch protection, CODEOWNERS, and secure repository practices.
• Knowledge of AI-specific supply-chain risks, such as hallucinated dependencies, poisoned tool descriptions, and compromised MCP servers.
• Experience delivering technical workshops, facilitating engineering groups, or leading practical knowledge-sharing sessions for experienced technical audiences.
• Professional fluency in English.

Nice to have

• Experience working in regulated environments such as insurance, finance, or healthcare.
• Familiarity with frameworks and standards such as OWASP Agentic Top 10, OWASP MCP Top 10, NIST AI RMF, ISO 42001, or the EU AI Act.
• Experience with AI security audit trails, incident response, injection testing, or guardrail regression testing.
• Experience creating AI usage policies, security checklists, or other practical security guidance for engineering teams.