Product Security Engineer for AI Systems

Design and build AI-native security systems that embed intelligent, autonomous controls into the software lifecycle. This role lives at the intersection of application security, machine learning, and developer productivity, and will lead efforts to enable continuous risk discovery, intelligent remediation, and secure deployment for applications, infrastructure, and AI workloads. You will join the Product Security core team and help shape secure development practices for AI-first products.

About micro1: micro1 is an AI data lab that converts subject matter expertise into high-quality training data, evaluations, and feedback for frontier models. The platform connects global experts across domains to scale human intelligence for AI.

• Architect and implement AI-powered security systems that autonomously detect, triage, and remediate vulnerabilities across applications, infrastructure, and AI workloads.
• Develop agentic security workflows that use LLMs and machine learning for tasks such as code review, threat detection, vulnerability correlation, root-cause analysis, and automated fix generation.
• Integrate intelligent security controls, AI guardrails, and continuous validation into CI/CD pipelines to evolve the Secure Software Development Lifecycle.
• Lead threat modeling for distributed systems, AI platforms, retrieval-augmented generation architectures, model-serving infrastructure, data pipelines, and autonomous agents.
• Design security frameworks to protect AI systems from prompt injection, model abuse, data poisoning, adversarial attacks, and sensitive data leakage.
• Build behavioral detection models and risk engines to detect synthetic identities, document fraud, account takeover attempts, and other adversarial activity in customer onboarding and KYC workflows.
• Apply machine learning and contextual risk scoring to reduce alert fatigue, prioritize findings, and drive autonomous remediation decisions.
• Partner with engineering, platform, and AI research teams to embed security as a native capability throughout product development.
• Scale security engineering culture through mentorship, technical leadership, and enablement programs that promote secure AI development practices.

• Demonstrated experience building or applying AI and LLM-powered security solutions, such as agentic workflows, autonomous remediation systems, vulnerability discovery, or security copilots.
• Deep expertise in Application Security, Product Security, or Security Engineering, backed by a strong software development background.
• Hands-on experience integrating enterprise security tooling into automated developer workflows and AI-driven orchestration platforms, for example Snyk, Checkmarx, GitHub Advanced Security, Semgrep, Wiz, or Lacework.
• Strong understanding of modern security architecture, cloud-native systems, APIs, microservices, and distributed computing environments.
• Familiarity with OWASP Top 10, OWASP Top 10 for LLM Applications, secure AI development practices, and emerging AI threat models.
• Advanced programming proficiency in Python, plus at least one additional language such as Go, Java, Rust, or Node.js.
• 8+ years of relevant experience in security engineering, application security, or related roles.

• Employment type: Full-time.
• Location: Remote.
• Team: Product Security core team, contributing to long-term platform and product security initiatives.

• Salary range: $250, 000 to $400, 000 per year.

• Applicants should be prepared to demonstrate and discuss relevant experience. Interview topics and technical exercises may include designing or implementing behavioral detection models and risk engines to identify synthetic identities, document fraud, account takeover attempts, and other adversarial activity within onboarding and KYC workflows.