Job Description

Role Title: InfoSec Expert

Role Type: Contractor

Location: Remote

micro1 is engaging InfoSec Experts to contribute to a high-impact project for one of our customers in the enterprise SaaS space. 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 define comprehensive red-teaming workflows and adversarial scenarios targeting SaaS and cloud-based environments.
Conduct hands-on penetration testing and adversarial threat modeling across platforms such as Microsoft 365, Google Workspace, Slack, GitHub, and Snowflake.
Act as a senior reviewer, critically evaluating the quality and depth of red-teaming exercises and deliverables.
Identify and document potential vectors for misuse or manipulation of AI agents, including prompt injection, privilege escalation, data exfiltration, and destructive actions.
Contribute practical insights for developing and vetting security controls, policies, and detection strategies relevant to real-world SaaS environments.
Collaborate with other cybersecurity professionals, providing detailed written and verbal feedback on findings and improvements.
Support benchmarking initiatives by creating adversarial scenarios that reflect contemporary threats and attack methodologies.

Preferred Qualifications

Extensive hands-on experience in security domains such as red teaming, penetration testing, application/cloud security, or security engineering.
Deep understanding of enterprise SaaS security concepts including identity, RBAC/permissions, and data governance.
Direct familiarity with Microsoft 365, Google Workspace, Slack, GitHub, and Snowflake from a security evaluation perspective.
Demonstrated ability to think adversarially about how AI and SaaS platforms could be exploited or compromised.
Strong written and verbal communication skills, enabling clear articulation of complex security issues and recommended remediations.
Proven track record of practical, real-world impact in security projects—beyond simply listing experience on a resume.
Bonus: Prior experience in AI/LLM security or adversarial testing of agent-based systems.

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About Micro1

Micro1 is building the essential infrastructure for the next generation of artificial intelligence, moving beyond the limitations of static datasets to create a dynamic ecosystem where models truly learn to think and act. At its core, the company understands that the path to frontier intelligence isn't paved with synthetic data alone; it requires the nuance, judgment, and contextual awareness that only expert human guidance can provide. By positioning itself at the intersection of human expertise and advanced reinforcement learning, Micro1 is tackling the hardest problem in AI today: teaching models not just to answer questions, but to reason through complexity and take meaningful actions in unpredictable, real-world environments.

This mission comes to life through Realm, Micro1's flagship training environment. Realm functions as a high-fidelity simulation ground where AI agents are immersed in scenarios that closely mirror the messiness of actual human workflows. Rather than relying on abstract benchmarks, Realm forces models to engage in agentic actions, multi-step decisions, digital navigation, coding, and problem-solving that require genuine comprehension. It is within these realistic sandboxes that world-class human data is generated, creating a continuous feedback loop where expert annotators observe, correct, and guide model behavior. This process does more than just fine-tune outputs; it fundamentally elevates a model's underlying reasoning architecture, ensuring that the intelligence developed in training holds up when deployed into the wild.

But training is only half the equation. Micro1 recognizes that the true test of an AI system lies in its production performance, which is where Cortex enters the picture. Cortex is a contextual evaluation platform designed to move beyond superficial accuracy metrics and provide a granular, real-time view of how agents behave in live settings. It doesn't just flag errors; it surfaces the underlying context behind failures, revealing why an agent struggled with a particular user intent or environmental variable. This insight is invaluable for engineering teams, as it transforms evaluation from a passive checkpoint into an active improvement tool. With Cortex, companies can catch degradation early, understand the nuances of edge cases, and feed those learnings directly back into Realm for retraining, creating a virtuous cycle of continuous advancement.

Ultimately, Micro1 is not merely a data lab or an evaluation tool it is a comprehensive intelligence engine that connects the entire lifecycle of model development. From the expert human feedback that sharpens raw capability, to the realistic RL environments that forge robust agentic behavior, to the contextual oversight that ensures reliability in production, Micro1 provides the integrated foundation that AI labs and enterprises desperately need. As the industry races toward truly autonomous systems, Micro1 stands as the critical bridge between laboratory breakthroughs and dependable, real-world impact, ensuring that frontier models do not just perform well on paper, but deliver genuine value in the complex, dynamic world they are meant to serve.