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Senior Staff Product Manager - Splunk AI Foundations (Remote, USA)

Cisco
10 Locations$191k – $281kPosted 13 June 2026

Job Description

The application window is expected to close on: 06/13/2026 Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received . Senior Staff Product Manager - Splunk AI Foundations Splunk 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. 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. We function as the core engine for AI innovation, enabling builders to deploy AI at scale while maintaining rigorous security, governance, and observability. Our team is a diverse group of experts and engineers who thrive in a fast-paced, collaborative, and innovation -driven environment. We are excited to be at the forefront of AI-native digital resilience, solving complex challenges that bridge the gap between raw data and intelligent, agentic workflows. Our work is essential to the larger vision of powering the future of secure, automated infrastructure. Your Impact : As the Senior Staff Product Manager, you will serve as the architect of the AI Development Factory, a unified platform that empowers builders to ingest data, curate training sets, and deploy enterprise-grade AI models. You will define the strategic roadmap for end-to-end AI/ML lifecycles, ensuring our tools provide seamless, secure, and performant model development. You will drive the integration of robust governance and guardrails to control model behavior and ensure compliance with security policies. Additionally, you will build and scale platform observability layers to allow users to trace performance and debug complex multi-step workflows. Your success will be measured by your ability to bridge the gap between raw data lakes and production-grade AI, ultimately shipping a world-class platform to our 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. Why Cisco? At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint. Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to ... (truncated, view full listing at source)
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