AI Security Engineer

AI Security Engineer (Agentic SOC)

In this role, you will:

• Build & Deploy Agents: Design, test, and deploy autonomous and semi-autonomous AI agents that integrate natively with our enterprise security stack (SIEM, EDR, XDR, and Threat Intel feeds).

• Code the Playbooks: Translate traditional, human-centric SOC playbooks and analyst workflows into deterministic and heuristic agentic pipelines (using DAGs and multi-agent routing).

• Optimize RAG Pipelines: Design, optimize, and maintain production-grade Retrieval-Augmented Generation (RAG) workflows to inject real-time security context, network topology, and historical incident logs into agent prompts.

• LLM Performance Engineering: Continuously evaluate, benchmark, and optimize LLM performance, context window utilization, latency, and cost-efficiency across various models (OSS and commercial).

• Design Human-in-the-Loop (HITL): Collaborate deeply with Tier 3 Analysts and Threat Hunters to engineer seamless HITL handoff mechanisms, ensuring agents safely escalate complex anomalies to humans.

• Secure the AI: Implement robust security boundaries around our LLM architecture, mitigating risks like prompt injection, data poisoning, model tool-abuse, and addressing the OWASP Top 10 for LLMs.

The Ideal Candidate:

• You are a Builder First: You take immense pride in shipping clean, production-grade, asynchronous code. You care about system architecture as much as model accuracy.

• Security-Curious or Security-Hardened: You bridge the gap between AI research and practical cybersecurity. You understand that an AI agent is only as good as the guardrails keeping it from deleting a production server during a false positive.

• Thrives in Ambiguity: Building an Agentic SOC means charting unknown territory. You love breaking down abstract, high-level security problems into concrete, execution-ready AI systems.

Basic Qualifications:

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies, OR a Master's degree in a related field plus at least 2 years of experience.

• At least 2 years of experience programming with Python, Go, Scala, or Java.

Preferred Qualifications:

• 3 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g., AWS, Google Cloud, Azure).

• Experience designing, developing, delivering, and supporting AI services, specifically within the domains of security operations or threat intelligence.

• Hands-on experience building multi-agent or complex orchestration systems using tools such as LangChain, LlamaIndex, AutoGen, CrewAI, or Semantic Kernel.

• Proven experience working with production Vector Databases (e.g., Pinecone, Qdrant, Milvus, or Weaviate) for semantic chunking, embedding generation, and metadata filtering.

• Experience deploying and scaling AI workloads in containerized cloud environments (AWS, Azure, or GCP using Kubernetes/EKS/AKS).

Are you ready to build the future of autonomous, agentic defense?