Cybersecurity AI Engineer

Main Purpose of Job:

As our Cybersecurity AI Engineer, you'll research, build, and deploy AI agents that automate security operations — from threat detection to incident response — reducing manual toil while keeping systems reliable and secure. This is an R&D-driven role at the intersection of cybersecurity, AI agent development, and SRE, ideal for someone who wants to build the next generation of autonomous security tooling rather than just operate existing ones.

Key Experiences:

• 3-5 years in cybersecurity/security engineering, with strong R&D orientation toward AI automation.
• Hands-on experience building AI agents for security tasks — agent architecture, tool-use, orchestration frameworks (LangChain, AutoGen).
• Experience fine-tuning/prompting LLM agents to automate SOC workflows (triage, investigation, remediation).
• R&D experience prototyping AI/ML techniques (RAG, multi-agent systems) into production-ready tools.
• Experience integrating AI models into security infrastructure (SIEM, SOAR, EDR) to automate manual processes.
• Experience testing/hardening AI agents against adversarial attacks (prompt injection, jailbreaks).
• Experience applying SRE principles to AI agents — reliability monitoring, SLIs/SLOs, safe rollback.
• Familiarity with MLOps/LLMOps for deploying agents — CI/CD, versioning, observability, IaC (Terraform, Kubernetes).
• Foundational knowledge of ML libraries (pandas, scikit-learn) and cloud AI platforms (SageMaker, Vertex AI).
• Understanding of AI agent governance — guardrails, human-in-the-loop, audit trails, NIST AI RMF.

Functional or Professional / Business Skills:

• Functional knowledge of AI agent frameworks, LLM orchestration tools, SIEM/SOAR platforms, and cloud AI/security infrastructure (e.g., SageMaker, Vertex AI, AWS Security Hub, Azure Sentinel).
• Familiar with AI governance frameworks, security policies, and standards governing agent deployment and autonomous system operations (e.g., NIST AI RMF, SOC 2).
• Strong analytical skills — able to assess security operational needs, design appropriate AI automation solutions, and identify opportunities to reduce manual toil through agentic tooling.
• Ability to collaborate effectively with Cybersecurity, Data Science, IT Security, Infrastructure, and third-party providers or development teams on R&D and production rollout of AI agents.

Skilled at influencing, resolving conflict, and negotiating with stakeholders at all levels — particularly when balancing automation autonomy against risk tolerance and human oversight requirements.