App Security Expert

Pay: $40 - $80/hour

Required Skills
OSWE
LLM security
AI-SAST evaluation
AppSec
Agent security architecture
About micro1
micro1 is a data lab that helps AI labs & Enterprises train foundational models and agents. We provide frontier evaluations and reinforcement learning environments to improve LLM capabilities, as well as contextual evaluations to monitor and improve AI agents in enterprise settings.

Our AI recruiting agent sources and vets domain experts for our data platform that enables rapid production of high-quality training data. Our research spans high-value, specialized domains (legal, medical, finance, coding, etc.), where expert-level data is the hardest to produce and most valuable for advanced model performance. Our pipeline performance system ensures both quality and velocity.

Role Title: App Security Expert

Role Type: Contractor

Location: Remote

micro1 is engaging App Security Experts to contribute to a customer’s dynamic project focused on real-world application security. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

Scope of Work

Design and implement small, purpose-built application fixtures with embedded security vulnerabilities or secure solutions, specifically addressing OWASP LLM risks such as Sensitive Information Disclosure and Excessive Agency.
Develop deterministic test cases and security-context manifests to robustly assess application security posture.
Create detailed hidden answer keys to enable accurate AI or scanner evaluation of vulnerable versus secure code.
Evaluate and iterate on pipeline methodologies to ensure synthetic tasks and fixtures are challenging yet realistic for AppSec assessment.
Document technical insights and methodologies, ensuring clarity in written feedback and communication.
Collaborate through clear and thorough written and verbal communication to share findings and review peer contributions.
Engage with agent-based security architecture and contribute to continuous improvement of the evaluation pipeline.

Preferred Qualifications

Extensive experience (ideally 5+ years) in application security, secure software development, or CyberSWE roles.
Strong understanding of OSWE, LLM security, AI-powered static analysis (AI-SAST), and AppSec best practices.
Proven track record designing or evaluating security architecture for traditional and agent-based applications.
Expertise in building, securing, and testing application codebases, including identifying and remediating advanced vulnerabilities.
Exceptional written and verbal communication skills, with a focus on precise technical documentation and collaborative feedback.
Experience with synthetic security fixtures and deterministic testing approaches is highly desirable.
Demonstrated ability to deliver thoughtful insights and actionable security recommendations in a remote contribution context.
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