LTS
LTS17h ago
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Agentic AI Security Engineer

United StatesUnited StatesRemotemid
OtherAi Security Engineer
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Quick Summary

Key Responsibilities

Secure Agentic AI Systems Design and implement security controls for autonomous and multi-agent AI systems. Secure agent orchestration, tool execution, memory, and external integrations.

Technical Tools
OtherAi Security Engineer

Responsibilities

~1 min read
  • Design and implement security controls for autonomous and multi-agent AI systems.
  • Secure agent orchestration, tool execution, memory, and external integrations.
  • Identify and mitigate emerging AI-specific attack vectors and vulnerabilities.
  • Secure Retrieval-Augmented Generation (RAG) pipelines, embeddings, vector databases, and enterprise knowledge repositories.
  • Design controls that prevent unauthorized knowledge access, data leakage, and information exposure.
  • Implement secure handling of sensitive enterprise and healthcare data throughout AI workflows.
  • Perform threat modeling for AI applications, agent architectures, prompts, APIs, and retrieval systems.
  • Assess risks associated with prompt injection, jailbreak attempts, indirect prompt attacks, tool misuse, hallucinations, data poisoning, model abuse, and adversarial inputs.
  • 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.
  • Help define organizational standards for responsible AI development and deployment.
  • 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.
  • Conduct security reviews of AI features before production deployment.
  • Promote secure AI engineering practices across the product organization.
  • 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.
  • Understanding of AI-specific security risks including:
    • Prompt injection
    • Jailbreaking
    • Data poisoning
    • Model abuse
    • Adversarial inputs
    • Hallucination mitigation
    • Sensitive data leakage
  • Experience with cloud security across AWS, Azure, or Google Cloud.
  • Strong programming experience in Python or TypeScript.
  • Excellent communication and collaboration skills.
  • A mindset of both a security engineer and a software engineer.
  • Experience with solving problems that don’t yet have established playbooks.
  • Ability to stay current with emerging AI threats and defensive techniques.
  • Experience with ownership of complex technical challenges.
  • Ability to collaborate effectively across engineering disciplines.
  • Capability to influence how secure AI systems are built in highly regulated environments.
  • Strong ability to balance innovation with responsible engineering.

Nice to Have

~1 min read
  • 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.
  • Experience supporting Federal Government or healthcare environments.
  • Familiarity with Zero Trust Architecture and secure DevSecOps practices.
  • Professional certifications such as CISSP, CCSP, Security+, GIAC, or cloud security certifications are a plus.
  • The Opportunity to support high-visibility federal missions
  • A culture that values innovation, growth, and collaboration
  • Access to cutting-edge tools and technologies
  • Comprehensive benefits for you and your family
  • A career path that rewards ambition and performance

If you’re ready to push boundaries, sharpen your skills, and join a team that is passionate about building what’s next, we’d love to meet you. Apply today and let’s build a future together!

 

LTS shares salary ranges to promote transparency. Compensation ranges are provided for informational purposes, and final compensation may vary based on experience, skills, location, and role requirements.

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.

Location & Eligibility

Where is the job
United States
Remote within one country
Who can apply
US

Listing Details

Posted
July 30, 2026
First seen
July 30, 2026
Last seen
July 31, 2026

Posting Health

Days active
0
Repost count
0
Trust Level
76%
Scored at
July 30, 2026

Signal breakdown

freshnesssource trustcontent trustemployer trust
LTS
LTS
greenhouse
Employees
30
Founded
2002
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LTSAgentic AI Security Engineer