Senior Security Engineer, AI Architecture Patterns

NVIDIA

. Develop shift-left solutions embedding security standards into AI-generated code .

Posted 10/16/2026full-timeRemote • United StatesSenior💰 $168,000 - $270,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in security engineering and AI tooling, with a strong focus on developing secure, enterprise-grade solutions. Proficient in Kubernetes, Python, and Go, with a solid understanding of CI/CD pipelines and security architecture.

Highest-signal resume keywords

Security EngineeringAI Coding AgentsKubernetesPythonCI/CD Pipelines

ATS Keywords

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Hard Skills

Security ArchitectureThreat ModelingControl SelectionIsolation BoundariesWorkload IdentitySecrets HandlingLoggingAuditMachine-Checkable SpecificationsEvaluation Harnesses

Soft Skills

Influencing Without AuthorityTechnical Trade-Off ExplanationTeam Capability Improvement

Tools & Technologies

HelmContainer Image HardeningStatic AnalysisPolicy-As-CodeSchema ValidationGit WorkflowsAutomated Publishing

Certifications & Qualifications

BS/MS in Computer ScienceEngineering

Industry Keywords

DevSecOpsDistributed SystemsEnterprise StandardsPrototype to ProductionSecurity Standards

Tech Stack

Tools & technologies

Distributed SystemsKubernetesPythonGo

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

Equity
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