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Principal Security Engineer, Product & AI

1 month, 2 weeks ago
United States
Full-time
Lead
Security Engineer
Cybersecurity
AWS Generative AI Go Java Kubernetes LLM Machine Learning Network Security Python PyTorch SIEM TensorFlow Terraform
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Marqeta

Marqeta

Marqeta is a pioneer in modern card issuing and payment solutions, offering businesses instant card issuance and payment processing through their innovative open API platform.

Diversified Financial Services
251-1K
Founded 2010
View All Jobs 20

Description

  • Lead product security engineering for the payment platform, including threat modeling, security architecture review, secure SDLC practices, and API security.
  • Build and mature the AI security program by developing genAI controls, securing ML pipelines, and supporting model evaluations with the Model Risk Office.
  • Provide security architecture oversight across infrastructure and enterprise security, including endpoint protection, network security, VPN, and corporate security controls.
  • Shape how security engineering scales through tooling, frameworks, security champions engagement, and partnerships with engineering teams.
  • Conduct security architecture reviews and threat modeling for new product features, APIs, and service integrations.
  • Define and maintain secure development lifecycle practices, including secure code review standards, API security patterns, and authentication and authorization frameworks.
  • Develop self-service security tooling and developer-facing guardrails that reduce friction while maintaining security posture.
  • Lead security strategy and risk assessment for AI/ML systems, including customer-facing AI products, fraud detection models, LLM integrations, and recommendation systems.
  • Perform security assessments of AI/ML model architectures, training pipelines, inference endpoints, and deployment infrastructure.
  • Partner with product security, infrastructure security, security operations, engineering, data science, and compliance, while mentoring security engineers and communicating risks to executive and board audiences.

Requirements

  • 10+ years of security engineering experience with demonstrated technical leadership across multiple security domains, or an equivalent combination of education and experience.
  • Deep product security expertise in threat modeling, security architecture review, secure code review, API security, authentication and authorization design, and secure SDLC practices.
  • Experience with or strong interest in AI/ML security, including adversarial attacks, model poisoning, prompt injection, data privacy, and AI supply chain threats.
  • Broad security fluency across infrastructure and enterprise security, including endpoint protection, network security, identity, and cloud security.
  • Experience working in cloud-native environments, with AWS preferred, and familiarity with AI/ML services such as Bedrock and SageMaker.
  • Proven ability to build security frameworks, tools, and programs from the ground up.
  • Strong programming skills in at least one language such as Python, Java, or Go, 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, including PCI DSS, SOX, SOC2, and NIST CSF.
  • Ability to communicate complex security risks to both technical and executive audiences.
  • Financial services or fintech experience is strongly preferred.
  • Experience securing payment processing systems, card issuing platforms, fraud detection models, or transaction monitoring infrastructure is preferred.
  • Hands-on experience with LLM security, including prompt injection mitigation, output filtering, RAG security, and agent security patterns, is preferred.
  • Experience with enterprise security platforms such as EDR, SIEM, identity providers, and network security tools is preferred.
  • Experience with ML frameworks such as PyTorch or TensorFlow, or a background in data science or machine learning engineering, is preferred.
  • Knowledge of AI governance, model risk management practices, and emerging AI regulatory frameworks such as the EU AI Act and NIST AI RMF is preferred.
  • Background in supply chain security, CI/CD pipeline security, or secure software composition analysis is preferred.
  • Experience with Kubernetes, containerized workloads, and Infrastructure as Code such as Terraform is preferred.
  • CISSP, CCSP, CISA, or other relevant security certifications are preferred.

Benefits

  • Remote-first Flexible First work model, with the role available anywhere within the United States or from the Oakland office.
  • Competitive base salary ranging from $218,300 to $321,000 depending on location tier.
  • Annual bonus eligibility tied to individual performance and company success.
  • Multiple health insurance options.
  • Flexible time off.
  • Retirement savings program with company contribution and after-tax contributions.
  • Equity in a publicly traded company plus an Employee Stock Purchase Program.
  • Family-forming benefits, fertility support, and up to 20 weeks of parental leave.
  • Free therapy sessions, financial and professional coaching, and legal advice.
  • Monthly stipend to support remote work.
  • Annual development dollars for learning and growth.

Interested in this position?

Apply directly on the company website

Apply Now

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