Principal Security Engineer, Product & AI

Marqeta Marqeta · Fintech · Job Requisition - Premium+/Premium/National · CyberSecurity

Principal Security Engineer focused on product security for a payment platform and building the AI security program for generative AI and ML capabilities. Responsibilities include threat modeling, securing APIs, building genAI controls, and ensuring AI-powered capabilities ship securely. Also provides security architecture oversight for enterprise and infrastructure security. This role partners with various security teams and serves as the security voice in the Model Risk Office. It's an individual contributor role with mentoring responsibilities.

What you'd actually do

  1. Lead product security engineering for our payment platform—owning threat modeling, security architecture review, secure SDLC practices, and API security across the engineering organization
  2. Help mature our AI security programdeveloping genAI controls, securing ML pipelines, and working alongside the Model Risk Office for model evaluations.
  3. Provide security architecture oversight across infrastructure and enterprise security—endpoint, network, VPN, and corporate security controls—ensuring technical standards are coherent across all security domains
  4. Shape how security engineering scales across the organization through tooling, frameworks, security champions engagement, and engineering partnerships

Skills

Required

  • 10+ years of security engineering experience with demonstrated technical leadership across multiple security domains
  • Deep product security expertise: threat modeling, security architecture review, secure code review, API security, authentication/authorization design, and secure SDLC practices
  • Experience with or strong interest in AI/ML security—understanding of risks including adversarial attacks, model poisoning, prompt injection, data privacy, and AI supply chain threats.
  • Broad security fluency across infrastructure and enterprise security—endpoint protection, network security, identity, and cloud security
  • Experience working in cloud-native environments (AWS preferred) with familiarity across AI/ML services (Bedrock, SageMaker, etc.)
  • Proven ability to build security frameworks, tools, and programs from the ground up
  • Strong programming skills in at least one language (Python, Java, Go, or similar) with the ability to read and review code across multiple languages
  • Experience with security assessment methodologies and risk management frameworks
  • Working knowledge of compliance and control frameworks relevant to financial services (PCI DSS, SOX, SOC2, NIST CSF)
  • Ability to communicate complex security risks to both technical and executive audiences

Nice to have

  • Financial services or fintech experience strongly preferred
  • Experience securing payment processing systems, card issuing platforms, fraud detection models, or transaction monitoring infrastructure
  • Hands-on experience with LLM security: prompt injection mitigation, output filtering, RAG security, agent security patterns
  • Experience with enterprise security platforms (EDR)

What the JD emphasized

  • AI security program
  • generative AI
  • ML capabilities
  • AI-powered capabilities
  • AI Security
  • AI/ML systems
  • genAI security controls
  • AI/ML model architectures
  • training pipelines
  • inference endpoints
  • AI-powered security tools
  • AI/ML security
  • LLM security

Other signals

  • building AI security program
  • securing generative AI and ML capabilities
  • AI-powered capabilities ship securely
  • AI Security
  • AI/ML systems
  • customer-facing AI products
  • fraud detection models
  • LLM integrations
  • recommendation systems
  • genAI security controls
  • AI/ML model architectures
  • training pipelines
  • inference endpoints
  • AI-powered security tools