Senior Security Engineer, AI Architecture Patterns

🕒 October 16

🏄 California, Florida, +3 more states – Remote

🏄 California – Remote 🐊 Florida – Remote 🌴 South Carolina – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $168k - $270.3k / year

⏰ Full Time

🟠 Senior

👮‍♂️ Cybersecurity / Security Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Develop shift-left solutions embedding security standards into AI-generated code • Convert written security standards into machine-enforceable formats • Engineer verification workflows for generated code and downstream release gating • Maintain evaluation harnesses, reference repositories, known-bad cases, and encouraged findings • Convert approved architecture patterns into secure reference implementations, templates, Helm charts, container images, and worked examples • Elevate AI solutions from prototypes to enterprise-grade products with versioning, observability, latency and cost budgets, access control, audit, graceful failure, and support/deprecation models • Set enterprise-grade architecture standards for AI tooling in a security context • Monitor qualification criteria, adoption, and outcomes • Collaborate with teams developing AI and automation solutions through build reviews, platform sharing, adoption, validation, and residual-risk closure

🎯 Requirements

• 8+ years in security engineering, platform engineering, product security, infrastructure security, DevSecOps, developer experience engineering, or software engineering for large distributed systems • Expertise with AI coding agents and tooling, including context and constraint injection, rules and scaffolds, plan-mode and tool integrations, and specification-guided development • Experience building evaluation harnesses and regression suites for non-deterministic systems • Proficiency in Kubernetes, Helm, container image hardening, identity, networking, and infrastructure primitives • Strong software engineering fundamentals in Python or Go • Experience with CI/CD pipelines, static analysis, code generation tooling, policy-as-code, schema validation, Git workflows, and automated publishing • Track record taking systems from prototype to production at enterprise standards • Security architecture experience including threat modeling, control selection, isolation boundaries, workload identity, secrets handling, logging, and audit • Ability to render security specifications machine-checkable • Ability to operate as both architect and engineer, review builds, explain technical trade-offs, influence without direct authority, and improve team capabilities • BS/MS in Computer Science, Engineering, or equivalent experience

🏖️ Benefits

• Equity • Benefits

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