LTS
Agentic AI Security Engineer
United States - Remote
Sponsorship not specifiedDetected 1 day ago
PythonVector DatabasesAWSAzureLLMsRAGAgentic AILangGraphAI OrchestrationA/B TestingCybersecurityZero TrustCommunicationCollaborationCISSP
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About the role
- This role focuses on securing AI systems, not simply securing infrastructure.
- LTS shares salary ranges to promote transparency.
Responsibilities
- Design and implement security controls for autonomous and multi-agent AI systems.
- Design controls that prevent unauthorized knowledge access, data leakage, and information exposure.
- Perform threat modeling for AI applications, agent architectures, prompts, APIs, and retrieval systems.
- Develop mitigation strategies that reduce AI-specific security risks while maintaining usability.
- Build guardrails that improve trustworthy AI behavior.
- Design policy enforcement, human-in-the-loop approval workflows, content filtering, and AI governance mechanisms.
- Design monitoring capabilities that detect abnormal agent behavior, misuse, prompt manipulation, and anomalous model interactions.
- Implement logging, traceability, and audit capabilities supporting explainability and regulatory compliance.
- Build mechanisms for continuous AI risk assessment and operational visibility.
- Partner with software engineers to integrate AI security into development workflows.
Requirements
- Bachelor's degree in Computer Science, Cybersecurity, Artificial Intelligence, Software Engineering, Information Security, or a related technical discipline (or equivalent professional experience).
- 7+ years of software engineering, cybersecurity engineering, AI engineering, or application security experience.
- Experience designing secure cloud-native or distributed software systems.
- Experience with Large Language Models (LLMs), AI applications, or Agentic AI platforms.
- Experience securing APIs, microservices, and enterprise applications.
- Knowledge of OWASP Top 10 and secure software development practices.
- Experience with cloud security across AWS, Azure, or Google Cloud.
- Strong programming experience in Python or TypeScript.
- Experience with solving problems that don't yet have established playbooks.
- Ability to stay current with emerging AI threats and defensive techniques.
Nice to have
- Experience securing Retrieval-Augmented Generation (RAG) systems.
- Experience with AI guardrails and policy engines.
- Familiarity with frameworks such as LangGraph, LangChain, CrewAI, Semantic Kernel, AutoGen, or LlamaIndex.
- Experience with vector databases including Pinecone, Weaviate, Qdrant, Milvus, or Azure AI Search.
- Experience implementing AI observability, evaluation, or monitoring solutions.
- Experience with NIST AI Risk Management Framework (AI RMF), Responsible AI practices, or AI governance frameworks.
- Familiarity with Zero Trust Architecture and secure DevSecOps practices.
- Professional certifications such as CISSP, CCSP, Security+, GIAC, or cloud security certifications are a plus.
Compensation
- ranges are provided for informational purposes, and final compensation may vary based on experience, skills, location, and role requirements.
Benefits
- Implement secure handling of sensitive enterprise and healthcare data throughout AI workflows.
- LTS is committed to offering eligible employees comprehensive benefits that will provide them with options intended to meet their needs and the needs of their family.
This listing is sourced directly from LTS's careers page and normalized into a canonical job model.