Cisco
Director, AI Engineering
$241K–$417K
San Jose, California, US · Onsite Only · Director · Full-time · Posted Oct 27, 2026
- Experience
- 15+ years with a bachelor’s degree, or 12+ years with a master’s degree; 5+ years of engineering management experience.
- Education
- Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field; alternatively, a Master’s degree with the stated experience alternative.
About the job
Leads engineering strategy and teams delivering production-grade agentic AI platforms and solutions for Cisco Customer Experience customer adoption and renewals.
What you'll do
- Lead end-to-end development and architecture of agentic AI solutions and their platform.
- Manage and mentor software, ML, and data engineering teams through full lifecycle delivery.
- Standardize tools and infrastructure; establish responsible AI, context engineering, and agent observability practices.
What they ask for
- Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field with 15+ years of software engineering experience, or Master’s degree with 12+ years.
- 5+ years of engineering management experience leading software and ML engineering teams.
- Programming experience in Python, Java, C++, or modern object-oriented languages.
- Experience building and scaling data-driven AI/ML systems, AI-native applications and agents, and deploying systems using LLMs, NLP, Generative AI, or Agentic AI architectures.
Nice to have
- Advanced degree (Master’s or PhD) in Artificial Intelligence, Computer Science, or Machine Learning.
- Experience architecting multi-agent orchestration pipelines and context engineering systems, or applying AI to enterprise customer success, adoption, or renewal workflows.
Pay
$250,600.00 to $362,600.00 USD base salary; $250,600.00 - $416,900.00 USD base salary; $241,400.00 - $371,000.00 USD base salary
Tools
Python, Java, C++, LLMs, NLP, Generative AI, Agentic AI
AI focus
Leads development and deployment of agentic AI solutions, platforms, autonomous agents, context engineering, multi-agent orchestration, and production AI/ML systems for customer adoption and renewals.
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