Senior Staff Product Manager - Splunk AI Foundations

About the Role

Splunk is seeking a Principal Product Manager to join its AI Foundations Team. This team is responsible for building the core models and tools that power Cisco and Splunk's entire product portfolio for global customers. In this role, you will play a crucial part in defining the roadmap for high-scale AI, with a particular focus on domain-specific models, agentic protocols, and orchestration platforms.

Meet The Team

The Splunk AI Foundations team is a high-impact group dedicated to delivering Gen AI and ML-based solutions that enhance Cisco and Splunk products. They serve as the core engine for AI innovation, enabling builders to deploy AI at scale while ensuring rigorous security, governance, and observability. Composed of diverse experts and engineers, the team thrives in a fast-paced, collaborative, and innovation-driven environment, working to bridge the gap between raw data and intelligent, agentic workflows.

Your Impact

As the Senior Staff Product Manager, you will be the architect of the "AI Development Factory," a unified platform designed to empower builders to ingest data, curate training sets, and deploy enterprise-grade AI models. Your responsibilities include:

• Defining the strategic roadmap for end-to-end AI/ML lifecycles, ensuring tools provide seamless, secure, and performant model development.
• Driving the integration of robust governance and guardrails to control model behavior and ensure compliance with security policies.
• Building and scaling platform observability layers to enable users to trace performance and debug complex multi-step workflows.
• Bridging the gap between raw data lakes and production-grade AI to ultimately ship a world-class platform to global customers.

Minimum Qualifications

• Bachelor’s degree plus 12 years of related experience, or Master’s degree plus 8 years, or PhD plus 5 years in Product Management with a focus on AI/ML platform products.
• Demonstrated 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.
• Proven 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.

Preferred Qualifications

• Advanced degree (Master's or Ph.D.) in a quantitative field or an MBA.
• Hands-on experience with the model and agent development lifecycle (e.g., PyTorch, Hugging Face, LangChain, LlamaIndex).
• Knowledge of MLOps and LLMOps principles within networking or cybersecurity.
• Experience building ecosystems, APIs, or SDKs for enterprise-grade AI platforms.
• Proven ability to drive adoption for builder-centric products and scale AI solutions from concept to market.