CI

Senior Engineering Manager, AI

Cisco
8 Locations$228k – $289kPosted 20 May 2026

Job Description

The application window is expected to close on: Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received . Meet the Team Splunk, a Cisco company, is building a safer, more resilient digital world with an end‑to‑end, full‑stack platform designed for hybrid, multi‑ cloud environments. Join the AI Models team at Splunk, where we advance the state of AI for high‑volume, real‑time, multi‑modal machine‑generated data — including logs, time series, traces, and events. We combine deep AI research expertise with the scale and operational excellence of Splunk and Cisco’s global engineering capabilities. Our work spans networking, security, observability, and customer experience — designing and deploying foundation models that enhance reliability, strengthen security, prevent downtime, and deliver predictive insights across Splunk Observability, Security, and Platform at enterprise scale. You’ll be part of a culture that values technical excellence, impact‑driven innovation, and cross‑functional collaboration — all within a flexible, growth‑oriented environment. Your Impact As a Senior Engineering Manager, AI , you will lead a high-performing team building advanced AI capabilities for code generation and developer productivity. You will help define the technical strategy, guide execution from research to production, and partner closely with product, platform, and engineering leaders to deliver scalable, reliable AI-powered experiences. This role is ideal for a leader with strong engineering management experience and deep technical fluency in machine learning systems, large language models, and production AI platforms. What You’ll Do Lead and develop a team of engineers and AI practitioners building intelligent code generation systems and related platform capabilities. Define and execute the technical roadmap for AI initiatives focused on code generation, agentic workflows, and developer tooling. Partner with cross-functional teams across engineering, product, and platform to bring AI innovations into production. Drive the design, development, evaluation, deployment, and operation of production-grade AI/ML systems. Establish best practices for experimentation, benchmarking, model evaluation, observability, reliability, and continuous improvement. Guide architectural decisions for distributed training, inference, tool integration, and scalable model-serving systems. Balance innovation with operational excellence, ensuring solutions meet high standards for performance, quality, cost efficiency, and maintainability. Hire, mentor, and grow technical talent while fostering an inclusive, high-accountability engineering culture. Influence long-term AI strategy and investment decisions across the broader organization. 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 grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere. We are Cisco, and our power starts with you. Message to applicants applying to work in the U.S. and/or Canada: The starting salary range posted for this position is $228,400.00 to $289,200.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits. ... (truncated, view full listing at source)
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