Forward Deployed Engineer, AI Security

Qualis; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Qualis is seeking a Forward Deployed Engineer to help enterprise customers secure their AI applications and agents. You will work directly with customer engineering teams to understand requirements, build production integrations, and verify security controls in their environment.

This is hands-on engineering work: writing code, troubleshooting deployments, and building reusable tools to simplify future integrations and maintenance. You will travel as needed to customer sites.

Qualifications

• Proven experience shipping and operating enterprise software or security integrations with customer teams.
• Strong Python and shell scripting skills with experience using APIs, Linux, containers, and at least one major cloud platform.
• Hands-on experience building or evaluating LLM applications or agents, including systems that use external tools.
• Understanding of AI security risks such as prompt injection, data leakage, and excessive permissions.
• Excellent communication with technical stakeholders and willingness to travel.

Responsibilities

• Design and build integrations between the security platform and customers’ AI applications, infrastructure, and development tools.
• Help customers see where AI agents are running and deploy controls that govern what those agents can do.
• Validate controls against requirements for detection, false positives, reliability, and latency.
• Diagnose issues across APIs, Linux, containers, cloud infrastructure, identity, and networking.
• Build reusable tooling and documentation, and train customer teams to operate and troubleshoot deployments.

Skills

Python

Shell scripting

APIs

Linux

Containers

Cloud platforms

LLM apps/agents

AI security risks

Communication with stakeholders

Willingness to travel

Tools

Docker

Job description

You will be a Forward Deployed Engineer to help enterprise customers secure their AI applications and agents. You’ll work directly with customer engineering teams to understand their requirements, build production integrations, and verify that security controls work in their environment.

This is a hands-on engineering role. You’ll write code, troubleshoot deployments, and build reusable tools that make future integrations easier to deliver and maintain.

What you’ll do

• Design and build integrations between the security platform and customers’ AI applications, infrastructure, and development tools.
• Help customers see where AI agents are running and deploy controls that govern what those agents can do.
• Validate controls against agreed requirements for detection, false positives, reliability, and latency.
• Diagnose issues across APIs, Linux, containers, cloud infrastructure, identity, and networking.
• Build reusable tooling and documentation, and train customer teams to operate and troubleshoot their deployments.

What you’ll bring

• Experience shipping and operating enterprise software or security integrations alongside customer engineering teams.
• Strong Python and shell scripting skills, with practical experience using APIs, Linux, containers, and at least one major cloud platform.
• Hands-on experience building or evaluating LLM applications or agents, including systems that use external tools.
• An understanding of AI security risks such as prompt injection, data leakage, and excessive permissions.
• Clear communication with technical stakeholders and willingness to travel for customer engagements.

Experience with AI gateways, managed agent platforms, endpoint software, or security telemetry is helpful.