Senior Product Security Engineer

Vertex Inc.•Remote - PA, PA

About The Position

This role requires practical, hands-on AI fluency. The ideal candidate is comfortable operating directly within the product development lifecycle—understanding how modern AI systems and agents behave, improve over time, and fail—and applying that understanding to product security decisions, acceptance criteria, and release readiness while owning and evolving broader product security strategy, governance, and risk management practices across the organization. Own and evolve major components of the Product Security strategy, translating product and business risk into actionable, measurable security programs with clear success metrics. Lead Secure-by-Design initiatives across product teams, embedding security requirements early in product and feature design, and defining secure design patterns, reference architectures, and guardrails that scale. Lead security architecture reviews, secure code reviews, threat modeling, and application penetration testing, with a focus on systemic risk reduction across a broad range of products. Establish and own security best practices for AI-enabled product features, model integration, and AI service architectures, including data handling, model access, and inference workflows. Lead AI-specific threat modeling addressing misuse, data leakage, supply-chain exposure, and abuse scenarios; define security controls and governance requirements specific to AI features and services. Evaluate the security implications of new AI technologies, tools, and models prior to adoption; embed responsible AI principles—traceability, privacy, bias awareness, transparency, and auditability—into product security decisions. Drive consistency in how product and AI risks are assessed, documented, tracked, and accepted across the organization. Serve as advisor to product and engineering on security risk, architectural trade-offs, and risk acceptance decisions. Mentor and provide technical leadership to other Product Security engineers and serve as an escalation point for complex security decisions.

Requirements

5+ years of experience in the security domain, including applying security controls to cloud-based technologies and implementing Product Security frameworks such as OWASP, CIS Benchmarks, and Cloud Security Alliance (CSA).
Proven track record of establishing security controls and governance requirements for AI-enabled features, including data handling, model access, and inference workflows.
Hands-on experience with AI product development security, including partnering with engineering and subject matter experts on model evaluation, tuning, and training.
Ability to define evaluation criteria for AI systems and interpret results to inform security requirements and release readiness decisions.
Experience with cloud governance principles and Product Security tooling, including SAST and DAST.
Demonstrated ability to lead threat modeling, secure code reviews, and application penetration testing for complex, cross-cutting security issues.
Demonstrated expertise in defining and scaling secure design patterns, reference architectures, and security guardrails across multiple product teams.
Technical acumen to experiment directly with AI tools and prototypes in support of faster product security validation.

Nice To Haves

Bachelor's degree in computer science or a related field; equivalent combination of education, training, and relevant professional experience accepted in lieu of a formal degree.
Experience with DevSecOps practices, zero trust design principles, and cloud incident response.
Experience contributing to the automation of security analysis and testing activities.
Track record of mentoring and providing technical leadership to security engineering teams.

Responsibilities

Own and evolve major components of the Product Security strategy, translating product and business risk into actionable, measurable security programs with clear success metrics.
Lead Secure-by-Design initiatives across product teams, embedding security requirements early in product and feature design, and defining secure design patterns, reference architectures, and guardrails that scale.
Lead security architecture reviews, secure code reviews, threat modeling, and application penetration testing, with a focus on systemic risk reduction across a broad range of products.
Establish and own security best practices for AI-enabled product features, model integration, and AI service architectures, including data handling, model access, and inference workflows.
Lead AI-specific threat modeling addressing misuse, data leakage, supply-chain exposure, and abuse scenarios; define security controls and governance requirements specific to AI features and services.
Evaluate the security implications of new AI technologies, tools, and models prior to adoption; embed responsible AI principles—traceability, privacy, bias awareness, transparency, and auditability—into product security decisions.
Drive consistency in how product and AI risks are assessed, documented, tracked, and accepted across the organization.
Serve as advisor to product and engineering on security risk, architectural trade-offs, and risk acceptance decisions.
Mentor and provide technical leadership to other Product Security engineers and serve as an escalation point for complex security decisions.