Splunk Security Core AI Agentic SOC Technical Lead
New
C
CiscoCybersecurity AI
This is a remote position, U.S. remote only.Full-TimeLead
Salary166,300 - 238,300 USD per year
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Job Details
- Experience
- 5+ years of experience developing, testing, and/or operating production software. Bachelors + 8 years of related experience, or Masters + 6 years of related experience, or PhD + 3 years of related experience.
- Required Skills
- PythonGoDistributed Systems
Requirements
- Have 5+ years of experience developing, testing, and/or operating production software.
- Have production software engineering experience developing in Python and/or Golang.
- Meet one of the stated education and experience combinations: bachelor's plus 8 years, master's plus 6 years, or PhD plus 3 years of related experience.
- Preferred: experience developing and operating production AI, agentic, or distributed systems.
- Preferred: experience with agent runtime, orchestration, shared APIs, context and memory, evaluation frameworks, experimentation systems, or production tracing.
- Preferred: experience with LLM and agent concepts including grounding and retrieval, planning, delegation, tool use, human oversight, behavioral evaluation, and regression analysis.
- Preferred: experience delivering containerized or cloud-native software across public cloud, on-premises, sovereign cloud, or air-gapped environments.
- Preferred: familiarity with SOC, SIEM, detections, incidents, investigations, response, and security concepts including identity, authorization, policy, privacy, tenancy, and auditability.
- Preferred: experience evaluating, integrating, or adopting shared technologies across large organizations.
- Preferred: responsible use of AI-assisted engineering across the software development lifecycle, with attention to validation, code quality, security, privacy, intellectual property, and human accountability.
Responsibilities
- Design and deliver components across shared Security AI runtime, orchestration, evaluation, and applied quality.
- Own features from requirements and design through implementation, testing, integration, deployment, and continuous improvement.
- Build reusable agent execution, governed tool-use, context and memory, shared API, telemetry, evaluation, trace-analysis, and experimentation capabilities.
- Develop agents and supporting systems for grounded reasoning, planning, delegation, human oversight, traceability, and safe failure handling.
- Use datasets, 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, including data residency, restricted connectivity, packaging, and upgrades.
- Implement identity propagation, authorization, tenant isolation, policy enforcement, privacy, auditability, and permission-aware actions.
- Diagnose failures across models, prompts, tools, data, orchestration, services, infrastructure, and product integrations.
- Collaborate with engineering, product, domain, deployment, quality, release, and support teams; mentor engineers and improve engineering practices.
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