Senior Security Engineer AI Agent Security & LLM Systems

Position Overview:

The Security Engineer / AI Agent Builder is responsible for designing, securing, and deploying agentic AI systems that operate safely within enterprise environments. This role blends security engineering, threat modeling, and applied AI system development-ensuring that intelligent agents operate reliably, securely, and in alignment with organizational policies.

Secure Agentic AI System Design:

• architect security controls (identity, network, runtime isolation, sandboxing, policy enforcement) for agent-based AI systems.
• Develop AIspecific threat models addressing agent misbehavior, adversarial prompts, data leakage, model tampering, and supplychain risks. Evaluate thirdparty AI tools, APIs, and agent frameworks for security compliance and risk.

Build & Deploy AI Agents:

• Design and implement autonomous AI agents using LLMs, APIs, orchestration frameworks, and multiagent systems.
• Build agent behavior logic including tooluse, routing, planning, fallbacks, and guardrails.
• Prototype and iterate AI agents in production, refining reliability, safety, and output quality based on realworld usage.

ProductionGrade Security Engineering:

• Develop security monitoring pipelines for agent executions and automate detection of anomalous or harmful agent behavior.
• Implement secure MLOps practices-including model lineage tracking, training data protection, and integrity controls.
• Perform vulnerability assessments, penetration testing, and redteaming of AI agents and underlying infrastructure.

CrossFunctional Collaboration:

• Work closely with AI research, product, engineering, cloud, and cybersecurity teams to ensure agents are performant, safe, and compliant.
• Translate business workflows into agent behaviors through scoping, discovery sessions, and requirements definition.

Standards, Governance & Best Practices:

• Establish secure development standards for agentic AI systems and contribute to enterprise AI governance frameworks.
• Publish internal best practices for agent security, including promptsecurity guidelines, LLM threat mitigation, and safetooling patterns.

Required Skills & Qualifications:

Technical Skills:

• 8+ years in cybersecurity engineering, application security, or cloud security.
• Handson experience with LLMs, AI/ML pipelines, vector databases, orchestration frameworks (AutoGen, CrewAI, LangGraph, etc.).
• Strong programming background (Python required; Java/C++ optional).
• Expertise in threat modeling, identity & access management, secure API design, and network segmentation.
• Familiarity with adversarial ML, model robustness testing, data poisoning defenses, and model evaluation.
• Experience deploying secure workloads in AWS/Azure/Google Cloud Platform.

Preferred Skills:

• Experience building autonomous agents or multiagent systems.
• Knowledge of AI governance, safety, and responsible AI frameworks.
• Background in cryptography, secure CI/CD pipelines, MLOps, and privacy preserving ML..