Senior Director, Enterprise AI Strategy & Global Engineering Productivity Leader

The application window is expected to close on: 11/09/2026

Meet the Team

Cisco’s Product Organization is at the forefront of powering the world’s connectivity, security, and digital infrastructure. As AI reshapes software engineering and enterprise operations, we are establishing an enterprise-wide AI Strategy & Productivity rigor to accelerate developer velocity, modernize software delivery lifecycles, and drive meaningful business transformation across our global product portfolio.

We are seeking a visionary, externally informed, and execution-oriented Sr. Director, AI Strategy & Engineering Productivity to partner directly with senior Product, Engineering, IT, Security & Trust, and Finance leaders to define and drive our multi-year Product AI vision. In this role, you will act as a strategic integrator—translating bottom-up developer innovation and top-down strategic mandates into a cohesive, high-impact AI productivity roadmap backed by proven practices from tier-1 engineering cultures.

Your Impact

As the Sr. Director of AI Strategy & Engineering Productivity, you will steer enterprise-wide transformation, define strategic investment focus, and establish the operational frameworks that empower thousands of Cisco engineers to build next-generation products faster and smarter.

• Distill long-range ambition into clear strategic priorities, market positioning, and a multi-year roadmap for AI-enabled productivity spanning developer tooling, coding harnesses, AI-DLC practices, and operational workflows.
• Establish a flexible operating model that bridges bottom-up developer innovation, strategic multi-functional initiatives, and executive mandates.
• Create a rigorous prioritization framework to evaluate trade-offs, model business impact, and transition Cisco from fragmented AI experimentation to scalable, repeatable, enterprise-grade capabilities.
• Partner with the Corporate Partnerships team to influence external AI model provider and tool vendor roadmaps, secure early access to frontier capabilities, and improve vendor ecosystem ROI.
• Collaborate closely with Engineering, Product, IT, Legal, Security & Trust, and Finance leaders—advocating for engineering constraints while constructively challenging the status quo to drive enterprise-wide alignment.
• Lead a vibrant, multi-functional community of practice across business units to establish shared standards for tooling, governance, and prioritization without sacrificing team autonomy.
• Design and operationalize comprehensive measurement frameworks that evolve beyond surface-level adoption metrics to rigorously quantify engineering throughput, code quality, developer satisfaction (DevEx), and realized financial value.
• Champion an AI-first, activated workforce grounded in trust, accountability, and psychological safety.
• Modernize engineering workflows, clarify technical ownership, and coach distributed teams through continuous change with high quality and early risk resolution.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Engineering, Business, or a related technical field or equivalent practical work experience.
• 15+ years of professional experience across software engineering, developer platforms, technical strategy, engineering leadership, or technology transformation.
• Experience with enterprise-scale strategies for software delivery modernization, developer productivity platforms, or AI-enabled technical transformations (peferrably with hyperscalers)
• Proven track record of influencing VP/SVP-level leaders, aligning multi-functional partners, and driving large-scale organizational change in a complex, matrixed technology environment.
• Demonstrable strategy background implementing modern software development lifecycle (CI/CD, security, observability, platform engineering) and practical applications of generative AI (AI coding assistants, agentic workflows, automated testing, or code modernization).

Preferred Qualifications

• Master’s degree or Ph.D. in Computer Science, Engineering, or Master of Business Administration (MBA)
• Proven ability to build compelling business investment cases, model trade-offs, and articulate technical value in terms of cost, operational risk, and customer impact.
• Experience driving AI developer productivity, platform engineering, or technical transformation at a top-tier technology company, cloud provider, or hyperscaler.
• Demonstrated success scaling AI developer tooling…