Director, Software Engineering | Enterprise AI Platforms, Infrastructure & Automation

Minimum Qualifications

• · Education: Bachelor's degree (B.Tech / B.E. / B.S.) in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, Artificial Intelligence, or a related quantitative STEM discipline from an accredited institution.
• · Professional Experience: 10+ years of progressive software engineering experience, including 3+ years leading high-performing technical engineering teams and 2+ years of hands-on production experience with LLMs, agentic workflows, or AI platforms.
• · Hands-on Coding Proficiency: Expert-level fluency in Python and modern TypeScript/JavaScript; strong working proficiency in Go, C++, or Rust for systems-level performance tuning.
• · AI & Systems Architecture: Deep practical experience with Model Context Protocol (MCP), LangGraph, LlamaIndex, vLLM, Triton Inference Server, PyTorch, and vector databases.
• · Modern Test & Performance Engineering: Demonstrated track record of designing large-scale distributed test harnesses, performance testing tools (k6, Locust, JMeter), browser automation (Playwright), and AI evaluation frameworks (Ragas, DeepEval, Promptfoo, Eval Studio).

Preferred Qualifications

• · Advanced Credentials: Master's degree (M.Tech / M.S.) or Ph.D. in Computer Science, Artificial Intelligence, Distributed Systems, Machine Learning, or Software Engineering from a premier tier-1 engineering institution or top global research universities).
• · GPU & Infrastructure Acumen: Solid understanding of GPU compute infrastructure, CUDA memory management, high-density server configurations, and container orchestration (Kubernetes, Docker).
• · Academic, Research, or Open Source Contributions: Demonstrated academic depth or research contributions in distributed systems, compiler optimization, GPU parallel computing (CUDA/Triton), formal software verification, major contributions to tier-1 open-source AI frameworks/benchmarks, or recognized technical patents in AI/systems engineering.
• · Player-Coach Leadership Archetype: Proven ability to lead from the front, write production code, conduct deep architectural reviews, and inspire an elite engineering culture without relying on bureaucratic middle management.
• · Enterprise Executive Communication: Excellent analytical, written, and verbal communication skills with the ability to influence, interact, and present technical architectures effectively across engineering, product, and executive leadership.
• 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.

Why Cisco?