Senior Network Security Architect

NVIDIA•Santa Clara, CA

1d•$196,000 - $379,500

About The Position

NVIDIA Enterprise Network Architecture team is seeking experienced candidates in the extensive domain of network security. Great foundations generating documentation for architectural planning, roadmaps, designs, evaluations, test plans, along with a passion for configuration standards will set you apart. Outstanding problem-solving abilities and a comprehensive understanding of network security protocols & standards, routing, switching, automation, and a deep understanding of fundamental network theory is also critical to your success at NVIDIA. This is a broad network security architecture role spanning traditional network security design, identity-driven access control, enablement of security products at scale, and emerging problem spaces like agentic AI workload isolation — with a strong emphasis on driving adoption, not just designing on paper.

Requirements

MS or PhD in Electrical Engineering, Computer Science, Computer Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, or equivalent experience.
12+ years of experience in building, managing and supporting large scale hybrid networks on the foundations of security.
Experience developing automation technology with Python, Ruby, Go or other languages used in infrastructure automation.
Advanced knowledge of NIST CSF, CIS controls, or MITRE ATT&CK frameworks.
Strong knowledge of networking protocols and encryption services and how these serve elevated security posture for a network.
Experience evaluating and testing new vendor platforms and in-house network initiatives for security issues.
Knowledge of cloud platforms like AWS, Azure, or Google Cloud, and their respective security practices and services.
Experience working cross-functionally with identity/IAM and product security teams to turn security capabilities into org-wide standards, not just point solutions.
Comfort operating in ambiguity on emerging problem spaces — including securing AI agent platforms where standards and precedent are still being written.

Nice To Haves

Experience with ML/AI as it relates to security analysis, vulnerability assessment and detection, threat modeling, malware detection, binary analysis, network analytics or other security-related research.
Experience working with heterogeneous security platforms and building them as code.
Experience driving org-wide adoption of a security standard or gate (e.g., getting a scanning/enforcement tool out of staging and into default production use across many teams).
Direct experience securing agentic AI / autonomous coding-agent infrastructure — sandboxing, egress control, and trust-domain isolation for workloads that complete AI-generated code with minimal human oversight.
Experience crafting segmentation for large-scale flat corporate and campus networks using internal firewalls, VLANs/VRFs, and NAC. You have a track record of gaining multi-functional sign-off and making the handoff operational, not just crafting it.

Responsibilities

Build and implement network protection frameworks, including firewalls, intrusion detection/prevention systems, VPNs and other security technologies.
Partner with Enterprise Security — working across IAM, network access control (NAC/802.1X), and Zero Trust identity/posture-based policy so that network access decisions are increasingly driven by who/what is connecting and its security posture, not just IP/VLAN placement.
Partner with Product Security (ProdSec) to enable NVIDIA's own security products and tooling for internal customers at scale — taking platforms validated in staging/pilot and driving them into org-wide production use (e.g., artifact/supply-chain scanning gates, access-control gateways, endpoint/network detection tooling), removing the friction that keeps good tooling stuck at "validated but not embraced."
Design network-level isolation for autonomous/agentic AI workloads ("autorun") and multi-tenant environments running disparate, co-located workloads at different trust levels — defining trust-domain boundaries, segmentation models, and long-term end-state architecture (e.g., firewall-based "chambers" today, migrating toward DPU-based zero-trust micro-segmentation as that capability matures) so that a compromised or malicious workload cannot reach other tenants or the broader corporate network.
Lead efforts to move NVIDIA's internal office and lab networks from a largely flat, implicitly-trusted model toward explicit east-west segmentation — internal/collapsed firewalls at key boundary points, a service-catalog-based access model, and a foundation for dynamic Zero Trust controls (posture, identity, application awareness) — without breaking existing lab/office workflows.
Research, evaluate, and recommend security solutions, products, and technologies that can enhance the network's security posture.
Partner and conduct security audits and penetration tests to assess the network's security and identify vulnerabilities.
Create and maintain documentation, including security policies, procedures, network diagrams, and multi-functional feasibility reviews that define clear ownership boundaries between network, identity, platform, and application-security teams.
Deliver guidelines, validated design standards, and direction on security standards/policies/roadmaps like Zero Trust to ensure consistent security practices across the organization. Provide domain expertise, consultation, and critical issue support.