Senior AI Security Platform Engineer (Agentic SOC)

Cisco Systems, Inc; San Jose (CA); Hybrid; USD 214.000 - 310.000; Vollzeit

Zusammenfassung

Cisco Systems, Inc. is seeking a Senior Staff Software Engineer to help build the Agentic SOC platform, spanning runtime, orchestration, and governance.

You will advance AI-driven security across Cisco and Splunk products, enabling reliable, auditable, and scalable security operations in cloud and air-gapped environments. You will lead design and implementation efforts, mentor engineers, and ensure safety, privacy, and correctness in live production systems while driving measurable improvements

Qualifikationen

• Experience building, testing, and operating production software.
• Experience with large-scale distributed or AI-enabled systems.
• Proficiency in Python or Go and strong software engineering foundations.

Aufgaben

• Shape technical direction for Agentic SOC capabilities across Cisco and Splunk products.
• Design reusable capabilities: agent runtime, orchestration, tool use, memory, evaluation, trace analysis, and quality gates.
• Translate SOC/SIEM/incident/response needs into shared mechanisms with security-domain experts.
• Architect for public cloud, on-premises, sovereign cloud, and air-gapped environments with strong privacy and auditability.
• Establish metrics-driven development with real data, simulations, and customer feedback.
• Mentor senior engineers and raise engineering standards across teams.

Kenntnisse

6+ years experience

Python

Go

Distributed systems

Ausbildung

Bachelor's degree + 10 years of related experience

Jobbeschreibung

Cisco Systems, Inc. is seeking a Senior Staff Software Engineer to help build the Agentic SOC platform, spanning runtime, orchestration, and governance.

You will advance AI-driven security across Cisco and Splunk products, enabling reliable, auditable, and scalable security operations in cloud and air-gapped environments. You will lead design and implementation efforts, mentor engineers, and ensure safety, privacy, and correctness in live production systems while driving measurable improvements