Splunk Security Core AI Agentic SOC, Technical Lead (remote)

The application window is expected to close on: 10/29/2026This is a remote position, U.S. remote only.

Help build the Agentic SOC of the future at Cisco Security!

You will work at the intersection of cybersecurity, artificial intelligence, and large-scale distributed systems to create trusted agentic capabilities that help security teams detect, investigate, and respond to threats more effectively. As part of the Security Core AI team, you will build and improve the shared AI systems behind these experiences—from agent platforms, orchestration, and governed tool use to evaluation, production trace analysis, and continuous quality improvement.

Your Impact

You will help deliver secure, reliable AI capabilities across cloud, on-premises, sovereign cloud, and air-gapped environments; collaborate with engineering teams across Cisco and Splunk; and apply AI tools throughout the software development lifecycle. This is an opportunity to turn rapidly evolving AI technologies into production-grade capabilities that operate at the scale, complexity, and trust level required by Cisco Security customers.

• Work independently on complex, ambiguous problems and serve as a technical resource within the team and partner teams.
• Design and deliver complex components across shared Security AI runtime, orchestration, evaluation, and applied quality.
• Own substantial features from requirements and design through implementation, testing, integration, deployment, and continuous improvement.
• Contribute to architecture and technical direction, using prototypes, evaluations, telemetry, and production evidence to guide decisions.
• Build reusable capabilities such as agent execution, governed tool use, context and memory, shared APIs, telemetry, evaluation frameworks, trace analysis, and experimentation systems.
• Apply familiarity with SOC, SIEM, detections, incidents, investigations, and response to engineer useful AI systems with domain SMEs.
• Develop agents and supporting systems for grounded reasoning, planning, delegation, human oversight, traceability, and safe failure handling.
• Use golden datasets, offline and online evaluations, production traces, trajectory analysis, regression gates, and model, prompt, or tool experiments to improve AI behavior.
• Design for cloud, on-premises, sovereign cloud, and air-gapped environments, addressing data residency, restricted connectivity, local model and tool availability, resource constraints, packaging, and upgrades.
• Implement identity propagation, authorization, tenant isolation, policy enforcement, privacy, audit-ability, and permission-aware actions.
• Integrate and promote adoption of shared Cisco and Splunk technologies, contributing Security requirements, feedback, and reusable improvements.
• Use shared contracts, adapters, and configuration to support product and deployment differences without unnecessary duplication.
• Leverage AI tools across requirements, design, coding, review, testing, documentation, debugging, release, and production analysis, with human validation and appropriate security, privacy, and intellectual-property controls.
• Make sound trade-offs across AI quality, latency, performance, cost, reliability, security, operability, and delivery.
• Diagnose failures across models, prompts, tools, data, orchestration, services, infrastructure, and product integrations.
• Write functional, maintainable, secure code and contributes to architecture, testing, review, and technical documentation standards.
• Collaborate across product, domain, deployment, quality, release, and support teams to land capabilities end to end.
• Mentor engineers, shares technical expertise, and improves engineering practices and knowledge sharing.

Minimum Qualifications

• 5+ years of experience developing, testing, and/or operating production software.
• Experience in software engineering in production, developing in Python and/or Golang
• Bachelors + 8 years of related experience, or Masters + 6 years of related experience, or PhD + 3 years of related experience.

Preferred Qualifications

• Experience developing and operating production AI, agentic, or distributed systems, including one or more of agent runtime, orchestration, shared APIs, context and memory, evaluation frameworks, experimentation systems, or production tracing.
• Demonstrated ability to design, implement, debug, and maintain complex, production-grade system
• Experience w…