Product Security Engineer
Status: Open
- Pay
- $250,000–$400,000
- Location
- Remote
- Employment type
- Full-time
- Openings
- 1
- Posted
- 2026-06-15
About this opportunity
Required skills
- AI & Security
- App Security Tooling
- LLM Security
- Programming Proficiency
What you'll do
- Architect and build AI-powered security systems that autonomously identify, triage, and remediate vulnerabilities across applications, infrastructure, and AI workloads.
- Develop agentic security workflows that leverage LLMs and machine learning for code review, threat detection, vulnerability correlation, root-cause analysis, and automated fix generation.
- Reimagine the Secure Software Development Lifecycle (SSDLC) by integrating intelligent security controls, AI guardrails, and continuous validation into CI/CD pipelines.
- Lead threat modeling initiatives for distributed systems, AI platforms, RAG architectures, model-serving infrastructure, data pipelines, and autonomous agents.
- Design security frameworks for protecting AI systems against emerging threats including prompt injection, model abuse, data poisoning, adversarial attacks, and sensitive data leakage.
- Build behavioral detection models and risk engines to identify synthetic identities, document fraud, account takeover attempts, and other adversarial activity within customer onboarding and KYC workflows.
- Apply machine learning and contextual risk scoring to reduce alert fatigue, prioritize security findings, and drive autonomous remediation decisions.
- Partner closely with engineering, platform, and AI research teams to ensure security is embedded as a native capability rather than a downstream function.
- Scale a culture of security engineering through mentorship, technical leadership, and enablement programs focused on secure AI development practices.
Requirements
- Demonstrated experience building or applying AI/LLM-powered security solutions, including agentic workflows, autonomous remediation systems, vulnerability discovery, or security copilots.
- Deep expertise in Application Security, Product Security, or Security Engineering with a strong software development background.
- Hands-on experience integrating enterprise security tooling (e.g., Snyk, Checkmarx, GitHub Advanced Security, Semgrep, Wiz, Lacework) into automated developer workflows and AI-driven orchestration platforms.
- Strong understanding of modern security architecture, cloud-native systems, APIs, microservices, and distributed computing environments.
- Deep familiarity with OWASP Top 10, OWASP Top 10 for LLM Applications, secure AI development practices, and emerging AI threat models.
- Advanced programming skills in Python and at least one additional language such as Go, Java, Rust, or Node.js.
- 8+ years of experience spanning Application Security, Software Engineering, Infrastructure Security, or related technical domains.
- Proven track record driving large-scale automation initiatives and transforming security programs from reactive operations to autonomous, intelligence-driven systems.
- Exceptional communication skills with the ability to translate complex technical and AI-related risks into strategic business decisions.
Preferred qualifications
- Experience securing AI products, foundation model platforms, inference infrastructure, or agentic systems in production environments.
- Background in applied machine learning, security data science, fraud detection, or behavioral analytics.
- Contributions to open-source security tools, AI security research, or industry thought leadership.
- Experience operating within high-growth technology companies, AI labs, or research-driven engineering organizations.
- Familiarity with emerging areas such as AI red teaming, model evaluation, agent security, autonomous penetration testing, or AI safety engineering.