Note: The job is a remote job and is open to candidates in USA. Ahura Workforce Solutions is recruiting for a telecommunications customer seeking a Cyber AI Engineer. The role leads the development and optimization of tools, processes, and workflows to identify and prevent AI-specific threats, while securing AI applications, platforms, agentic workflows, MCP-enabled architectures, and generative AI solutions in production. It also involves security assessments, threat modeling, remediation, governance, and cross-functional technical leadership.
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
- 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
- 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
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
- Contract-to-hire employment
Company Overview