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About the Role
Secure autonomous AI agents before and after they reach production by designing guardrails, performing security testing, and building governance controls for confident business deployment.
Responsibilities
- Design security guardrails for AI agents.
- Perform security testing on AI agent systems.
- Build governance controls for AI agent deployment.
- Explain AI risk clearly to various stakeholders.
Requirements
- 5+ years in security engineering (AppSec, cloud security, IAM or offensive security).
- 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.
- Proficiency in one of Go, TypeScript or Rust.
- Cloud security experience on AWS, Azure or GCP, including logging, detection and policy-as-code (e.g. OPA / Cedar).
Skills
- Security Engineering
- AppSec
- Cloud Security
- IAM
- Offensive Security
- LLM Security
- Agent-based Systems Security
- Prompt Injection
- Jailbreaks
- Data Exfiltration
- RAG Poisoning
- Identity and Access Controls
- OAuth 2.0
- OIDC
- Token Exchange
- Workload Identity
- Secrets Management
- LangGraph
- OpenAI Agents SDK
- CrewAI
- Model Context Protocol (MCP)
- Python
- Go
- TypeScript
- Rust
- AWS Security
- Azure Security
- GCP Security
- Logging
- Detection
- Policy-as-code
- OPA
- Cedar
- AI Risk Communication
Experience Level
- 5+ years in security engineering
- 1+ year securing LLM or agent-based systems
About the Company
- Belmont Lavan is hiring.