Senior Staff Product Manager - Splunk AI Foundations

Cisco is seeking a Senior Staff Product Manager to join Splunk’s AI Foundations Team, which builds foundation models and the infrastructure powering AI and machine-learning solutions across Cisco and Splunk products. The role will own the roadmap and productization of domain-specific foundation models, agentic workflow frameworks, evaluation systems, and inference platforms while ensuring scalability, performance, responsible AI, governance, and customer adoption.

Responsibilities:

• Drive Foundation Model Platform Strategy: Own the roadmap for the model substrate model families and sizes, context length, tokenization for machine data, fine-tuning and adapter APIs, embeddings and retrieval, and the SDKs that internal teams and external developers build on. Make and defend the build / adapt / buy decisions behind each capability
• Develop Specialized Models: Oversee the shipping of foundation models optimized for machine data, including zero-shot forecasting, anomaly detection, and log and trace understanding. Prove they outperform general-purpose LLMs and classical baselines through rigorous, reproducible evaluation before they reach GA
• Own Model Quality & Evaluation: Define what “good” means for each model: golden datasets, offline benchmarks, human review, and online experiments measuring forecast error, tool-call accuracy, grounding and hallucination rates, and regression gates that every checkpoint must clear before release
• Build Connectivity: Standardize AI skills for Cisco and Splunk products using common agentic protocols like MCP, creating universal connectors that expose tools, data, and context to any model in the portfolio
• Enable Agentic Workflows: Create the frameworks planning loops, tool schemas, memory, evaluation, and guardrails that let developers build autonomous agents capable of reasoning and planning across complex data environments
• Responsible AI & Governance: Advance the AI frontier responsibly by engaging with Compliance, Legal, and Finance on red-teaming and safety evaluations, model cards, training-data provenance and licensing, customer data isolation, and tenant-level privacy while owning the unit economics of inference (cost per token, GPU utilization, cloud margin)
• GTM & Ecosystem: Partner with Product Marketing and Sales to package these foundational capabilities for external customers, including consumption based pricing and metering, positioning against general purpose model providers, model documentation, and developer onboarding
• Customer Advocacy: Engage deeply with customers and design partners including on early checkpoints to develop insights into what is possible, uncover unarticulated needs, and ensure customer success

Requirements:

• Bachelor's degree plus 12 years of related experience in Product Management with a focus on AI/ML platform products; or Master's degree plus 8 years, or PhD plus 5 years
• Experience in the AI/ML lifecycle, including model fine-tuning (SFT/RLHF), orchestration architectures, and data ingestion pipelines (ETL/ELT)
• Experience implementing security protocols, compliance frameworks, and guardrails within AI or software development platforms
• Experience in building or managing observability tools, tracing, or monitoring systems for distributed systems or ML models
• Proficiency in SQL and Python for data analysis and managing large-scale data flows into AI-ready formats
• Advanced degree (Master's or Ph.D.) in a quantitative field or an MBA
• Hands-on experience with the end-to-end model development lifecycle: data curation, training and fine-tuning runs, evaluation, serving, drift monitoring, and retraining
• Knowledge of MLOps and LLMOps principles within networking or cybersecurity, including GPU capacity planning and deploying models in regulated or air-gapped environments
• Experience building AI ecosystems or managing partnerships with hyperscalers and model providers, spanning open-weight and frontier models, licensing, and co-development