Senior Lead Security Engineer, AI
On-site · Columbus, Ohio, United States
Job Summary
Lead end-to-end design and delivery of AI security solutions for cyber use cases; build secure LLM/RAG services; establish secure AI engineering standards; create evaluation harnesses; partner to stand up reusable AI components; implement drift and quality monitoring; collaborate with governance to meet documentation and attestations; mentor engineers; publish playbooks and safe prompt libraries; drive a roadmap of flagship capabilities (e.g., SOC triage assistant, controls automation agent, DevSecOps code copilot); possess 7+ years in software/security, 3+ years in production ML/LLM systems, strong Python and at least one of Java/Scala/TypeScript, familiarity with SIEM/EDR/SOAR/IAM/ITSM, LLM guardrails, PyTorch/TensorFlow, LangChain/LlamaIndex, and secure SDLC practices.
Required Qualifications
- Minimum 7 years of software/security engineering, including hands-on experience in one or more of: detection engineering, SecOps, AppSec/DevSecOps, or cloud security
- Minimum 3 years building and operating applied ML/LLM systems in production (RAG pipelines, embeddings, fine-tuning/specialization, vector databases, model serving)
- Proficiency in Python and at least one of: Java, Scala, or TypeScript; experience with microservices, APIs, containers, and Kubernetes
- Familiarity with SIEM, EDR, SOAR, IAM, and ITSM integrations; streaming/data engineering with Kafka or similar
- Experience with LLM orchestration and guardrails (prompt engineering, injection defense, tool calling, safety filters)
- Hands-on with ML/LLM ecosystems: PyTorch or TensorFlow; scikit-learn; LangChain/LlamaIndex; ONNX/Triton/Ray
- Strong understanding of secure SDLC, privacy, and data protection; ability to partner with governance to meet documentation and monitoring requirements
- Demonstrated ability to ship secure, reliable AI features with clear metrics and post-deployment monitoring
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