Staff Network Security Architect
Zoox Inc.
Job Description
Job Description
Zoox's Network Security team architects and defends the digital borders of the company, from corporate offices to engineering labs and product/mission environments. As Staff Network Security Architect, you own the target-state design for how Zoox segments, connects, and controls trust across enterprise IT, OT and lab networks, and hybrid cloud (AWS, GCP). You set the standards other teams build to, you are the security design authority on new infrastructure, and you are accountable for the coherence of the whole picture rather than the health of any one platform. You'll partner closely with Network Engineering, IT, Product Security, Hardware, and Software Engineering, and you'll influence far more systems than you personally operate.
In This Role, You Will...- Own Zoox's network security reference architecture across corporate, data center, lab/OT, and edge environments, and define the segmentation and trust model that everything else is built against
- Serve as the security design authority for new infrastructure: run design reviews and threat models early enough to change the design, and define the criteria under which a design is approved, conditionally approved, or rejected
- Translate security frameworks into buildable engineering standards. Map controls to NIST CSF 2.0, NIST 800-53, and ISO 27001 (IEC 62443 a plus for OT/lab), and turn them into reference patterns, guardrails, and acceptance criteria engineers can implement without interpreting policy
- Define the zero-trust and identity-to-network strategy, including 802.1X/certificate-based NAC, PKI trust hierarchy, ZTNA and remote access, and how non-human and headless lab/vehicle assets are authenticated and authorized
- Architect secure hybrid and multi-cloud connectivity (CloudWAN, SD-WAN, transit and inspection architectures, cloud-native controls) and define where inspection, enforcement, and logging belong
- Drive secure-by-design into the delivery path: encode standards as Terraform modules, policy-as-code, and CI/CD guardrails so the secure pattern is the default one, not a review gate
- Own data flow and trust boundary analysis for sensitive environments, including vehicle data, lab telemetry, and third-party and vendor connectivity
- Own the governance side of architecture: risk articulation for leadership, exception and compensating control decisions, architecture decision records, and the multi-year roadmap that retires legacy patterns
- Set technical direction and raise the bar across the team through mentorship, design review, and written standards rather than through direct ownership of day-to-day operations
- 10+ years in network and security engineering, including 4+ years in an architecture or technical-lead role where you owned designs others implemented
- Demonstrated ownership of an enterprise-scale segmentation or zero-trust architecture from concept through adoption, including what you changed when it met reality
- Ability to reason about security frameworks as design inputs, not audit artifacts: fluency with NIST CSF 2.0, NIST 800-53, and ISO 27001, and a track record of turning them into engineering standards and evidence
- Depth in threat modeling and secure-by-design for network and infrastructure, including data flow analysis, trust boundaries, blast radius, and failure modes
- Strong platform grounding to keep designs buildable: next-gen firewalls (Palo Alto, Fortinet), AWS NFW, IDS/IPS, NAC/802.1X, PKI, VPN, ZTNA (Zscaler, Prisma Access, or equivalent), and core protocols (TCP/IP, BGP, OSPF, VLAN, TLS/PKI)
- Cloud network security depth in AWS and/or GCP, including inspection architecture, cloud-native enforcement, and IaC delivery with Terraform
- OT, ICS, robotics, automotive, or manufacturing network security experience (IEC 62443, Purdue model, or equivalent)
- Autonomous vehicle or safety-critical systems exposure
- Certifications: CISSP-ISSAP, SABSA, TOGAF, CCIE Security, PCNSE, AWS Security Specialty
- Experience applying AI/ML to network or cloud security (anomaly detection, behavioral analytics, LLM-assisted design review or policy analysis)
Base Salary Range
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
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Accommodations
If you need an accommodation to participate in the application or interview process please reach out to View email address on ziprecruiter.com or your assigned recruiter.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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