Note: The job is a remote job and is open to candidates in USA. Ahura Workforce Solutions is seeking a Cyber AI Engineer for a telecommunications customer. The role drives the development and optimization of tools, processes, and workflows to predict, detect, assess, and prevent AI-specific threats while supporting the secure adoption of AI technologies across the enterprise. The engineer will assess, secure, and remediate vulnerabilities in AI applications, platforms, agentic workflows, MCP-enabled architectures, and generative AI solutions in production environments.
Responsibilities
- The Cyber AI Engineer will drive the development and optimization of advanced tools, processes, and workflows to predict, detect, assess, and prevent AI-specific threats
- This hands-on technical leadership role combines deep expertise in cybersecurity, AI security architecture, threat modeling, and security assessments to help ensure the safe adoption of AI technologies across the enterprise
Skills
- A Bachelor's or Master's degree in Computer Science, Engineering, Cybersecurity, or a closely related discipline is required
- 10+ years of experience in cybersecurity engineering, application security, cloud security, or AI security within enterprise environments
- Expertise in Python, R, Java, or similar programming languages
- Deep understanding of machine learning, large language models (LLMs), agentic architectures, and AI application security
- Demonstrated experience performing security assessments, threat modeling, and remediation activities for AI applications, AI platforms, or generative AI solutions
- Hands-on experience identifying and mitigating AI-specific threats, including prompt injection, data leakage, model abuse, insecure tool access, agent privilege escalation, and unauthorized data exposure
- Experience performing security reviews of AI systems, agent-based workflows, MCP-enabled architectures, APIs, and enterprise AI integrations
- 3+ years of experience with Azure or AWS cloud-native services, architectures, and tools
- Expertise in enterprise architectures, including cloud-native, AI, and distributed application security patterns
- Advanced knowledge of security and governance frameworks, including NIST AI-RMF, ISO42001, and OWASP Top 10 for LLM Applications
- Strong communication skills with the ability to explain complex technical concepts and remediation strategies to both technical and non-technical stakeholders
- Experience securing Agentic AI systems, multi-agent architectures, and autonomous workflows
- Experience securing or assessing Model Context Protocol (MCP) architectures, tool integrations, and agent communication frameworks
- Experience conducting AI security testing, red teaming, penetration testing, or architecture reviews of AI applications
- Demonstrated ability to lead cross-functional technical teams
- Experience implementing AI security controls, guardrails, monitoring, and governance solutions in production environments
Benefits
- Remote work arrangement
Company Overview