Security Engineer

Belmont Lavan

. Secure autonomous AI agents before and after they reach production .

Posted 11/5/2026full-timeTexas City • Texas • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in security engineering with a focus on securing AI agents and LLM systems, including hands-on experience with attack techniques and identity access controls. Proficient in cloud security practices and capable of communicating AI risks effectively to diverse stakeholders.

Highest-signal resume keywords

Security EngineeringLLM Attack TechniquesIdentity And Access ControlsCloud SecurityPython Programming

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Applicant Tracking System Keywords

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Hard Skills

Security EngineeringLLM Attack TechniquesIdentity And Access ControlsPython ProgrammingGo ProgrammingTypeScript ProgrammingRust ProgrammingCloud SecurityPolicy-As-CodeSecrets Management

Soft Skills

Clear Communication

Tools & Technologies

LangGraphOpenAI Agents SDKCrewAIModel Context ProtocolAWSAzureGCP

Industry Keywords

AppSecCloud SecurityIAMOffensive SecurityGovernance Controls

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPythonRustTypeScriptGo

About the role

Key responsibilities & impact

Secure autonomous AI agents before and after they reach production
Design guardrails for AI agents
Attack AI agent systems to identify vulnerabilities
Build governance controls enabling confident deployment of AI agents
Work between AI engineering and security

Requirements

What you’ll need

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