Product Security Engineer

SaidGig; New York (NY); Remote; USD 250,000 - 400,000; Full time

Job summary

SaidGig is seeking an experienced security leader to shape AI-native security engineering, blending application security, ML, and developer productivity. You will enable continuous risk discovery, intelligent remediation, and secure deployment throughout the software lifecycle.

The role focuses on architecting AI-powered security systems, integrating Snyk/Checkmarx/GitHub Advanced Security into automated workflows, and leading threat modeling across distributed systems.

Qualifications

• Demonstrated experience building or applying AI- or LLM-powered security solutions.
• Deep expertise in application security and security engineering with strong software background.
• Hands-on experience integrating enterprise security tools into automated workflows and AI orchestration.
• Strong knowledge of modern security architecture, cloud-native systems, APIs, and microservices.
• Advanced programming ability in Python and at least one additional language.

Responsibilities

• Architect and build AI-powered security systems that identify, triage, and remediate vulnerabilities.
• Create agentic security workflows using LLMs and ML for code review and remediation.
• Integrate AI guardrails and continuous validation into CI/CD pipelines.
• Lead threat modeling for distributed systems and AI platforms.
• Design protections against prompt injection and data leakage.
• Build risk engines for fraud and adversarial activity in onboarding and KYC.

Skills

AI security

LLM workflows

Security engineering

Python

Threat modeling

Tools

Snyk

Checkmarx

GitHub Advanced Security

Semgrep

Wiz

Lacework

Job description

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.