Solutions Engineer - Splunk (Remote)

Splunk Agent Observability Solutions Engineering Team Member

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.

Your Impact

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 Qualifications

• 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 LangGraph, OpenAI Agents SDK, Crew AI, AutoGen, or equivalent tools).

• Experience of Generative AI architectures, including Retrieval-Augmented Generation (RAG), tool calling/function execution, multi-agent coordination, and latency optimization, and LLM Failure modes(Hallucinations, bias, and prompt injection.

• Minimum 2 years of experience or 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).

Preferred Qualifications

• Proficiency in Python or TypeScript, along with experience utilizing modern AI and data libraries (such as Pandas, Streamlit, LangChain, HuggingFace, 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 (or equivalent practical professional experience). THIS JOB DESCRIPTION DOES NOT APPLY FOR EMPLOYEES IN AUSTRIA, BELGIUM, FRANCE, GERMANY & NETHERLANDS