Solutions Engineer - Splunk; Remote

The application window is expected to close on: 10/27/2026

The application window is expected to close on:
October 26, 2026

NOTE:

Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.

This role can be performed anywhere in the Pacific Coast region of the United States.

The Splunk Agent Observability Solutions Engineering team at Cisco powers the enterprise adoption of next-generation Generative AI evaluation, automated guardrails, and real-time runtime telemetry. We serve as the technical authority guiding Global 2000 enterprises to safely develop, benchmark, and scale autonomous multi-agent systems and mission-critical LLM applications. Our team culture is deeply collaborative, intellectually curious, and customer-obsessed, combining cutting-edge GenAI research with proven enterprise pre-sales engineering rigor.

Operating at the forefront of the Cisco and Splunk AI integration, you will collaborate with leading AI architects and engineering executives to pioneer production-grade trust, safety, and performance across modern enterprise AI infrastructure.

Lead in-depth technical discovery and architectural alignment with enterprise AI architects, data science leaders, and executive decision-makers to evaluate their GenAI stack and agentic observability requirements. Deliver high-impact technical demonstrations and customized reference architectures showcasing real-time LLM benchmarking, multi-agent evaluation, tokenomics optimization, and automated safety guardrails. Own the end-to-end scoping, technical milestones, and execution of customer Proof of Concepts (PoCs) to establish definitive technical wins and accelerate sales cycles.

Act as a strategic bridge between enterprise field engagements and Cisco/Splunk Product and Engineering teams, synthesizing customer feedback to guide future product roadmap priorities.

• Minimum 3+years of professional experience in technical pre-sales engineering, solutions architecture, or customer-facing technical consulting within AI/ML, data analytics, or enterprise software.
• Experience or knowledge building, deploying, or architecting workflows with agentic orchestration frameworks (such as Lang Graph, OpenAI Agents SDK, Crew AI, Auto Gen, or equivalent tools).
• Experience of Generative AI architectures, including Retrieval-Augmented Generation (RAG), tool calling/function execution, multi-agent coordination, and latency optimization, and LLMFailure modes(Hallucinations, bias, and prompt injection.
• Minimum 2years of experienceor equivalent experience scoping, instrumenting, and executing technical Proof of Concepts (PoCs) to a definitive win, aligned to customer business outcomes and technical champions
• Exceptional verbal and written communication, with the ability to convey complex AI concepts to both hands-on ML practitioners and C-suite executives (CTOs, CDOs, VPs of Engineering).
• Ability to travel between 15% and 25% for on-site customer workshops, Executive Briefing Centers (EBCs), and industry conferences (such as Splunk .conf and Cisco Live).

• Proficiency in Python or Type Script, along with experience utilizing modern AI and data libraries (such as Pandas, Streamlit, Lang Chain, Hugging Face, or OpenAI SDK).
• Experience rapidly prototyping (including "vibe coding") externally facing agentic applications, interactive demos, or production AI workflows.
• Prior professional experience as a Machine Learning Engineer, Data Scientist, or Software Engineer prior to transitioning to technical pre-sales.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical Engineering, Mathematics, or a related technical discipline…