Full-Time

Agentic AI Security Engineer

LTS

LTS

201-500 employees

Builds, deploys, sustains mission-critical federal IT

No salary listed

Remote in USA

Remote

Bachelor's

Category
IT & Security (1)
Required Skills
LLM
Microsoft Azure
Python
Threat modeling
RAG
TypeScript
Microservices
AWS
Google Cloud Platform

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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.
  • 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.
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. Identify and mitigate emerging AI-specific attack vectors and vulnerabilities.
  • Protect AI Models and Knowledge Systems: 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.
  • AI Threat Modeling: 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.
  • Responsible AI & Governance: 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.
  • AI Observability & Monitoring: 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.
  • Secure AI Development: 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.
Desired Qualifications
  • 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.

LTS provides both consulting and hands-on implementation for mission-critical needs in government and health, including disaster response, healthcare kiosks, occupational health, and federal IT work. Its approach combines program management, systems integration, and operations support to design, build, deploy, and sustain infrastructure and programs in the field. The company differentiates itself with end-to-end delivery across the full project lifecycle for government and health contexts, backed by experience across federal, state, local, and tribal levels and an emphasis on regulatory and security requirements. Its goal is to turn plans into durable, operational programs that keep communities safe and healthy.

Company Size

201-500

Company Stage

N/A

Total Funding

N/A

Headquarters

Herndon, Virginia

Founded

2005

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Simplify Jobs

Simplify's Take

What believers are saying

  • Lindsay Goldberg grew LTS revenue and EBITDA over 150% from 2020 to 2025.
  • Fifteen acquisitions and all-50-state coverage give Velocity immediate national scale.
  • Rail, renewable diesel, and generator fueling deepen cross-sell into mission-critical customers.

What critics are saying

  • Wind Point merged LTS into Velocity Rail in July 2025, eliminating standalone independence.
  • Commodity fuel delivery faces margin pressure if customers insource fueling or switch distributors.
  • Integration across 18,000 customers and 30,000 sites risks service failures and churn.

What makes LTS unique

  • 1998-founded LTS became North America's largest mobile on-site refueling operator by 2025.
  • LTS serves trucking, rail, marine, and emergency power without branch depots.
  • Its truck-to-truck model and 1,200 specialized vehicles create dense route economics.

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Benefits

Remote Work Options

Flexible Work Hours

Company News

Benzinga
Jul 22nd, 2025
LTS Sold to Velocity Rail Solutions

Lindsay Goldberg has completed the sale of Liquid Tech Solutions (LTS) to Velocity Rail Solutions. Under Lindsay Goldberg's ownership since 2020, LTS grew revenue and EBITDA by over 150%, expanded to all 50 states, and executed 15 strategic acquisitions. The transaction terms were not disclosed. Financial advisors included Harris Williams, UBS Investment Bank, and Citizens Capital Markets & Advisory.