Security Engineer

Drive the development and optimization of advanced AI architectures (cloud/hybrid), software, tools, processes, and workflows to predict, detect, and prevent AI specific threats. This hands-on technical leadership role combines deep research in AI security with close collaboration across teams to integrate AI capabilities into robust cybersecurity architectures.

Key Responsibilities

• Design, develop, and optimize AI/AI Security specific architectures, software, threat models, tools, solutions for threat identification, prediction, and prevention.
• Implement and secure agentic and MCP architectures, neural networks, and AI techniques to enhance threat detection, monitoring, and risk scoring.
• Integrate AI security tools and technologies across AI architectures, collaborating with data scientists, security engineers, and other stakeholders.
• Analyze AI security risk scoring and incident data to refine and improve AI architectures and methodologies.
• Provide technical leadership and mentorship to junior engineers in Agentic and MCP architectures.
• Ensure alignment and compliance with industry standards (NIST AI-RMF, ISO42001, OWASP Top 10 for LLM), and advanced security architectures (Agentic, MCP).
• Stay abreast of emerging trends and advancements in AI and cybersecurity.

Required Qualifications

• A bachelor's or master's degree in computer science, engineering, or a closely related discipline is required.
• 5+ years of experience in AI and cloud-focused architectures and cybersecurity in an enterprise environment.
• 8+ years deep hands-on low/high level software development expertise in Python, R, Java, C or similar programming languages.
• Deep hands-on understanding of agentic frameworks (LangGraph, LangChain, Crew, OpenClaw etc.,), and AI orchestration.
• Hands-on experience with AI security technologies (intrusion detection, anomaly detection, threat intelligence).
• 5+ years’ experience in Azure or AWS cloud native services, architectures, and tools.
• Expertise in enterprise architecture (including Cloud-native and AI architecture patterns).
• Advanced knowledge of security and governance frameworks (NIST AI-RMF, ISO42001, OWASP Top 10 for LLM).
• Strong communication and collaboration skills.

Preferred Qualifications

• Experience with agentic and model context protocols (MCP) architectures.
• Demonstrated ability to lead cross-functional technical teams.
• Track record of published research or thought leadership in AI security.