The application window is expected to close on: 07/22/2026
Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.
Distinguished Engineer, Splunk AgenticOps and AI Engineering TransformationLocation: Remote, West Coast hours preferred
Meet the Team Splunk's AgenticOps and AI Engineering Transformation team is focused on making AI a practical, governed part of real security, observability, and operational workflows. The team connects Splunk's telemetry, topology, identity, risk, platform, and Cisco network/application context so customers can investigate faster, understand root cause more clearly, and act safely. You will work with a lean, senior, cross-functional group spanning engineering, product, architecture, AI, security, observability, platform, and Cisco-connected experiences. The vibe is technical, pragmatic, customer-grounded, and highly collaborative, with a strong bias toward turning promising ideas into durable product capabilities. What makes the work exciting is the chance to shape how enterprise AI moves beyond chatbots into trusted, evidence-based operational assistance.
Your Impact Define the technical direction for AgenticOps foundations across Splunk's unified security and observability portfolio. Shape governed AI workflows that use telemetry, topology, identity, ownership, risk, network context, and product knowledge to help customers investigate, triage, respond, and remediate with confidence. Partner with product and engineering leaders to identify the highest-value product wedges, guide prototypes, clarify architectural tradeoffs, and move ideas into shippable capabilities. Develop reusable platform patterns for MCP/tool access, evidence chains, permissions, audit-ability, approvals, policy enforcement, evaluation, and safe action. Drive AI-assisted engineering transformation across planning, coding, review, testing, release readiness, support, incident learning, and operations so teams gain execution leverage without lowering Splunk's quality bar.
Minimum Qualifications - Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience.
- 15+ years of experience building, leading, or architecting large-scale software systems used by enterprise customers.
- Experience designing or operating data-intensive, distributed, AI-assisted, agentic, or operational software systems.
- Production software engineering experience, including writing or reviewing production-quality code.
- Experience defining architecture for platform capabilities such as workflow orchestration, tool access, permissions, audit logs, approvals, policy enforcement, or safe automation.
- Experience delivering technical direction that changes how multiple engineering teams build, test, support, operate, evaluate, or ship software.
Preferred Qualifications - Experience with AI-assisted development, agentic workflows, LLM application architecture, AI evaluation, prompt/tool orchestration, or human-in-the-loop systems.
- Experience with telemetry, observability, security analytics, time-series systems, event processing, or data platforms.
- Experience with graph systems, entity identity, semantic layers, topology, temporal modeling, or operational context modeling.
- Experience building products for cloud, hybrid, and customer-managed deployment environments.
- Ability to influence across engineering, product, architecture, field, executive, and customer-facing teams while mentoring senior engineers through ambiguous technical decisions.
