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Principal Product Manager - Splunk AI FoundationsSplunk is looking for a Principal Product Manager to join our AI Foundations Team! We are building the core models and tools that power our entire product portfolio for global customers. In this role, you will help define the roadmap for high-scale AI, focusing on domain-specific models, agentic protocols, and orchestration platforms.
The Team The Splunk AI Foundations Organization delivers Gen AI and ML-based solutions that enhance Cisco and Splunk products. We introduce new offerings that help customers deploy AI at scale responsibly, keeping security and observability at the center of every model.
Your Impact As a Principal Product Manager for the Splunk AI Foundations Team, you will be the architect of the
"AI Engine Room" that powers the future of Splunk and Cisco's joint vision for AI-native digital resilience. You will be instrumental in crafting the core substrate of our platform-developing the foundational models, protocols, and orchestration tools that not only drive our internal Platform, Security, and Observability portfolios but are also shipped as a world-class platform to our global customers and developer ecosystem.
In this role, you will lead the productization of domain-specific foundation models (such as the
Cisco Time Series Model). By building agentic workflow frameworks, you will empower a new era of "self-driving" operations where autonomous agents collaborate with humans to investigate and remediate incidents in real-time. Your work will bridge the gap between groundbreaking AI research and production-grade enterprise software, ensuring that every AI interaction is performant, scalable, and built on a foundation of Responsible AI and trust.
What You'll Do - Drive AI Platform Strategy: Lead the roadmap for AI foundational elements, including tools, frameworks, APIs and SDKs used by both internal teams and external customers.
- Develop Specialized Models: Oversee the shipping of models optimized for machine data, ensuring they outperform general-purpose alternatives through rigorous evaluation.
- Build Connectivity: Standardize AI skills for the Cisco products using protocols like MCP to create universal connectors for AI workflows.
- Enable Agentic Workflows: Develop tools that allow developers to 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 to ensure products meet ethical AI standards, data privacy, and security while addressing financial goals (e.g., cloud margin).
- GTM & Ecosystem: Partner with Product Marketing and Sales to package these foundational capabilities for external customers, including pricing, positioning, and developer documentation.
- Customer Advocacy: Engage deeply with customers to develop insights into what is possible and uncover unarticulated needs to ensure customer success.
Qualifications - Bachelors + 12 years of related experience, or Masters + 8 years of related experience, or PhD + 5 years of related experience, or
equivalent related work experience in Product Management, with a focus on prioritizing AI/ML platform products.
- Technical Depth: Solid understanding of AI/ML architectures (LLMs, Deep Learning), training, and evaluation. Familiarity with Vector DBs and Agentic Workflows.
- Data Skills: Proficiency in SQL and Python for data analysis, along with experience in large-scale data pipelines.
- Growth Mindset: Proven ability to drive adoption for developer-centric products and scale AI solutions from concept to market.
- Collaborative Leadership: Experience working with early design partners to validate and iterate on new features.
- Communication: Ability to translate complex AI roadmaps into clear strategic narratives for partners.
- Education: Bachelor's degree in an AI related technical field like CS, Data Science, or Engineering.
Preferred Skills - 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.
- Knowledge of MLOps principles within networking or cybersecurity.
- Experience building AI ecosystems or managing partnerships with hyperscalers and model providers.
