Description
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. 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.
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.
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).
Benefits
- Medical, dental and vision insurance
- 401(k) plan with a Cisco matching contribution
- Paid parental leave
- Short and long-term disability coverage
- Basic life insurance
- 10 paid holidays per full calendar year
- 1 paid day off for employee’s birthday
- Paid year-end holiday shutdown
- 4 paid days off for personal wellness
- 16 days of paid vacation time per full calendar year (non-exempt employees)
- Flexible vacation time off program (exempt employees)
- 80 hours of sick time off provided on hire date and each January 1st thereafter
- Optional 10 paid days per full calendar year to volunteer