Senior Lead AI Security Engineer

What you'll do

• Design and deliver end-to-end AI solutions for cyber use cases including data integration, model development, and monitoring.
• Build secure LLM/RAG services and ML pipelines integrated with security tools like SIEM, XDR, and SOAR.
• Establish engineering standards for prompt security, input/output validation, PII masking, and secret handling.
• Create evaluation harnesses using golden datasets, adversarial prompts, and safety metrics to ensure model quality.
• Develop reusable AI infrastructure components such as LLM gateways, vector stores, and governance workflows.
• Implement drift monitoring, define SLAs, and create incident response runbooks for AI-enabled services.
• Manage compliance by partnering with risk teams to meet documentation, validation, and attestation requirements.
• Drive the development of flagship capabilities like SOC triage assistants and DevSecOps code copilots.

What we're looking for

• Minimum 7 years of software or security engineering experience including detection engineering, SecOps, AppSec, or cloud security.
• Minimum 3 years of experience building and operating applied ML/LLM systems in production.
• Proficiency in Python and at least one other language such as Java, Scala, or TypeScript.
• Experience with microservices, APIs, containers, and Kubernetes.
• Familiarity with SIEM, EDR, SOAR, IAM, and ITSM integrations along with Kafka or similar streaming technologies.
• Expertise in LLM orchestration and guardrails including prompt engineering, injection defense, and safety filters.
• Hands-on experience with ML/LLM ecosystems such as PyTorch, TensorFlow, scikit-learn, LangChain, LlamaIndex, ONNX, Triton, or Ray.
• Strong understanding of secure SDLC, privacy, data protection, and meeting governance requirements for AI systems.