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Belmont Lavan Ltd

Agent Security Engineer

Belmont Lavan Ltd Texas City, Texas, United States

IT System Custom Software Development · 2-10 employees

19 h ago
Remote security Senior (5-10 yrs) Full-time United States
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About the role

You will design security guardrails and governance controls to secure autonomous AI agents throughout their lifecycle. This role involves performing offensive security testing and collaborating between AI engineering and security teams.

What they look for

Security Engineering AppSec Cloud Security IAM Offensive Security LLM Security Prompt Injection Jailbreaks OAuth 2.0 OIDC Secrets Management LangGraph Python Go TypeScript Rust

Requirements

Candidates must have 5+ years of experience in security engineering with at least 1 year specifically focused on LLM or agent-based systems. Proficiency in Python, cloud security, and identity access management protocols is required.

Full description

Belmont Lavan is hiring an Agent Security Engineer to secure autonomous AI agents before and after they reach production. Agents now call tools, hold credentials and act on live systems, so they need the controls we already expect for people and services: identity, least-privilege access, monitoring and testing.

You will sit between AI engineering and security. You will design the guardrails, attack the systems yourself, and build the governance controls that let the business deploy agents with confidence.

  • 5+ years in security engineering (AppSec, cloud security, IAM or offensive security), with at least 1 year securing LLM or agent-based systems
  • Hands-on knowledge of LLM attack techniques: prompt injection, jailbreaks, data exfiltration via tools, RAG poisoning
  • Experience designing identity and access controls: OAuth 2.0 / OIDC, token exchange, workload identity, secrets management
  • Working knowledge of agent frameworks and protocols such as LangGraph, OpenAI Agents SDK, CrewAI or Model Context Protocol (MCP)
  • Strong coding skills in Python, plus one of Go, TypeScript or Rust
  • Cloud security on AWS, Azure or GCP, including logging, detection and policy-as-code (e.g. OPA / Cedar)
  • Ability to explain AI risk clearly to engineers, risk teams and executives

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