About this role
Role Overview
Shape AI-native security engineering by building autonomous security capabilities that scale with modern software development. This role blends application security, machine learning, and developer productivity to enable continuous risk discovery, intelligent remediation, and secure deployment throughout the software lifecycle.
Key Responsibilities
- Architect and build AI-powered security systems that identify, triage, and remediate vulnerabilities across applications, infrastructure, and AI workloads.
- Create agentic security workflows using LLMs and machine learning for 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, RAG architectures, model-serving infrastructure, data pipelines, and autonomous agents.
- Design protections against prompt injection, model abuse, data poisoning, adversarial attacks, and sensitive-data leakage.
- Build behavioral detection models and risk engines for 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 support autonomous remediation decisions.
- Partner with engineering, platform, and AI research teams to embed security as a native capability.
- Provide mentorship, technical leadership, and enablement focused on secure AI development practices.
Qualifications
- Demonstrated experience building or applying AI- or LLM-powered security solutions, including agentic workflows, autonomous remediation, vulnerability discovery, or security copilots.
- Deep expertise in application security, product security, or security engineering, supported by a strong software development background.
- Hands-on experience integrating enterprise security tools such as Snyk, Checkmarx, GitHub Advanced Security, Semgrep, Wiz, or Lacework into automated developer workflows and AI-driven orchestration platforms.
- Strong knowledge of modern security architecture, cloud-native systems, APIs, microservices, and distributed computing environments.
- Deep familiarity with the OWASP Top 10, OWASP Top 10 for LLM Applications, secure AI development practices, and emerging AI threat models.
- Advanced programming ability in Python and at least one additional language, such as Go, Java, Rust, or Node.js.
- At least 8 years of relevant experience.
Work Terms
- Full-time remote position.
Compensation
- Annual compensation of $250, 000 to $400, 000.