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RoleSummary

Splunk is seeking a senior individual contributor to serve as the technical lead for the AI agents that make our technical sellers more productive, setting direction through thought leadership and influence across field teams. The role spans the full agent lifecycle across multiple platforms: setting best practices for cost, performance, design, and integrations; deciding which agents are built where; completing the last-mile build; maintaining a subset in production; and directing and reviewing a contractor who builds additional agents. You will combine agentic engineering (designing and building agents) with agentic operations (running them reliably, safely, and cost-effectively) as the single technical authority guiding quality from design through production. Your immediate mission is to deliveran initial3 to 5 agents that streamline technical sellers' daily workflows, freeing them to spend moretimecustomer-facing and advancing Splunk's revenue and customer-success goals.

Responsibilities

Agentic Platform Strategy (Architect)

Reference Design & Standards:Advise on the end-to-end design for agentic systems across platforms, contributing inputs to the reference designs, patterns, and standards agents are built against, and informing system-level decisions on howagentsreason, integrate, and scale.

Cross-Platform Best Practices:Define, document, and evangelize best practices for cost, performance, design, and integrations across the organization's agent platforms, so teams build consistently and avoid duplicated effort.

Platform Selection & Build Allocation:Guidewhich agents are built on which platform, balancing capability, cost, integration fit, security, and maintainability, and set the criteria the organization uses to decide.

Contractor Direction & Review:Set technical direction fora contractorbuilding agents, specifying what to build and where, and reviewing their work for quality, security, and adherence to standards. (Technical direction and review, not people management.)

Technical Thought Leadership & Influence:Serve as the recognized technical authority for agentic systems across field teams, contributing to reference designs and standards, mentoring engineers, and driving alignment with IT, Engineering, Cloud Operations, Security, Product, and field stakeholders through influence.

Strategic Impact:Advance Splunk's revenue and customer-success goals by increasing technical sellers' customer-facing time and making the agents behind demonstrations and Field Solutions Apps more capable, reliable, safe, and cost-effective.

Agent Delivery & Engineering (Build)

Deliver Seller-Productivity Agents:Own delivery ofan initial3 to 5 production agents that streamline technical sellers' daily workflows, prioritizing theusecases that return the most selling time and measurably reduce manual effort.

Last-Mile Build & Integration:Complete the last-mile build of agents, wiring up tools, Model Context Protocol (MCP) servers and clients, data sources, and integrations, and hardening them from prototype to dependable production use.

Agent Design & Orchestration:Translate the reference design into working agentic systems with evaluation and guardrailsdesigned infrom thestart, anddefine retrieval (RAG) and tool-integration strategies that keep agents grounded andaccurate.

Agentic Operations (Operate)

Observability & Monitoring:Establishcomprehensive logging, monitoring, andalerting foragents in production. Because agents make non-deterministic decisions, ensure deep visibility intoagenthealth, behavior, and performance, and lead root-cause analysis when agents fail.

Performance & Cost Evaluation:Track resource consumption across agentic workloads, including API usage and token limits across LLMs. Define and monitor SLOs/SLIs, manage cost-per-task economics, and drive model-routing and efficiency decisions that keep performance high and spend predictable.

Governance & Guardrails:Define the boundaries that keep agents safe, within budget, and compliant with security and regulatory standards,establishingpolicy, permissions, audit trails, and human-in-the-loop checkpoints so every agent action is bounded, traceable, and auditable.

Continuous Optimization & Maintenance:Maintaina subset of production agents, resolving regressions and keeping them current as platforms and models evolve, while using telemetry and evals to refine prompts, tools, topologies, and guardrails. Validate changes in simulation before release andautomate awaymanual toil.

Qualifications

Technical Skills:

3+ years of software, ML, or platform engineering experience, including a demonstratedtrack recordof leading technical direction through influence (no direct-report or people-management requirement)

Proven ability to act as a technical authority and force multiplier (contributing to reference designs and standards, mentoring engineers, and driving adoption) without formal management authority

Hands-on experience designing and building production agentic systems, including multi-agent orchestration and Model Context Protocol (MCP) integrations

Experience selecting among and building across multiple agent platforms, with the judgment to match use cases to the right platform

Strong tool and API integration skills, including designing retrieval (RAG) strategies that keep agents grounded andaccurate

Experience building evaluation harnesses and offline/online evals, andvalidatingagentic systems in simulation before release

Experience implementing guardrails, policy and permission models, and audit trails for autonomous systems

Familiarity with token and cost management across multiple LLM providers, including model routing and fallback strategies

Experience directing and reviewing the work of contractors, vendors, or peer engineers through technical review (without formal management authority)

Hands-on experience operating agents in production, including observability and monitoring with Splunk and Splunk Observability (Splunk o11y)

Experience with Splunk products (Splunk Cloud/Enterprise, Splunk IT Service Intelligence, Splunk Observability, or equivalent) for telemetry, monitoring, and observability

Proficiencyin cloud-native architectures, preferably AWS

Experience in programming/scripting languages such as Python and Bash

Understanding of distributed systems, microservices architecture, and API design

Strategic & Business Skills:

Strong strategic thinking and ability to translate businessobjectivesinto technical roadmaps

Excellent communication skills with ability to present technical concepts to non-technical stakeholders

Track recordof delivering results in fast-paced, dynamic environments

Data-driven decision-making approach with focus on measurable outcomes

Core Valuesand Mindsets:

Commitment to Excellence:A dedication to delivering high-quality solutions, strengthening technical skills, and taking pride in continuous improvement to consistently raise the bar.

Adaptability / Flexibility:A growth mindset, openness to feedback, and the ability to respond effectively to new challenges and rapid change.

Collaboration:A strong teamplayer attitude, excellent communication skills, and a commitment to empowering colleagues and fostering an open, supportive environment.

Ownership:A proactive approach to improvement, accountability for outcomes, and a drive todeliver oncommitments without waiting for direction.

Innovation:A passion for creative problem-solving, technical rigor, and pushing boundaries whilemaintaininghigh standards.

Fun:An ability to embrace fun, celebratesuccess, and contribute to a positive and energetic culture where everyone can thrive.