Engineering Program Manager

Engineering Program Manager

As Engineering Program Manager within Cisco Cloud Security organization, you will be working very closely with the Software Engineering team, supporting cloud products and deliverables. You bring an AI-first Technical Program Management lens to everything you do, embedding artificial intelligence, machine learning, and intelligent automation into how programs are planned, executed, and delivered.

Besides solid program delivery and technical skills, you have proven experience in problem solving, managing multiple projects simultaneously, a deep understanding of cloud product development, strong background in CI/CD development model, and delivery of complex large-scale software projects.

You thrive in a fast-paced and demanding environment. You have the ability to think creatively and critically, lead through intellect, and are willing to roll-up your sleeves when needed. In addition, you are able to partner across a wide variety of functions. You have strong internal drive, a tenacious spirit, good communication skills and a collaborative method of working.

Key Responsibilities:

• Bring strong Technical Program Management expertise with an AI-first vision, pioneering the adoption of AI-driven tools, automation, and data-informed decision-making to accelerate program delivery and drive innovation across teams
• Support, track and manage complex program execution, cross-functional coordination, and inter/intra team communications to deliver outstanding, high quality program outcomes
• Track and maintain cross-functional dependencies/deliverables, work with other cross-functional groups within Cisco Security to manage dependencies and deliverables
• Provide timely issue resolution and critical path management; and facilitate good communication.
• Drive day-to-day program activities to meet overall program objective
• Be self-directed with the ability to review changes and weigh tradeoffs between engineering resources and operational improvements
• Provide weekly updates and offer multiple levels of status across a wide spectrum of individual contributors to executive management
• Drive an AI-first approach to program management, identifying and deploying AI/ML tools and intelligent automation to streamline planning, reporting, risk detection, and decision-making
• Partner with engineering teams to plan and deliver AI/ML-powered features, demonstrating data-driven insights and predictive analytics to improve program velocity, quality, and outcomes

Minimum Qualifications:

• Bachelor’s + 8 years, a Master’s degree + 6 years, or PhD + 3 years of complex program management (preferred in software cloud environments), using both agile and waterfall. Degree should be in Engineering, Computer Science or related technical field.
• 3+ years of experience applying AI/ML tools, GenAI assistants, and intelligent automation to program management.
• 3+ years of experience coordinating cross-functional projects, facilitating team meetings, and collaborating with geographically distributed teams.
• Prior experience in Lean Enterprise / Agile / Kanban practices and supporting tools.
• Experience with defect tracking applications like JIRA and business applications such as Word, Excel and Project.

Preferred Qualifications:

• Able to communicate well with cross-functional team members, be able to efficiently collaborate with and influence team members to achieve project goals, and contribute positively to the engineering community environment.
• Ability to understand, discuss / communicate technical concepts, with both technical and non-technical individuals.
• Ability to find opportunities to embed AI across the software delivery lifecycle.
• Working knowledge of cloud and network security concepts and technologies such as SASE, Security Service Edge (SSE), Zero Trust, DNS-layer security, secure web gateway (SWG), and firewall /cloud-delivered security.
• Familiarity with security compliance and certification frameworks (e.g., FedRAMP, SOC 2, ISO 27001, PCI DSS, GDPR) and experience supporting audit- or compliance-driven programs.
• Experience delivering programs in a DevSecOps environment, integrating security controls and testing into CI/CD pipelines and the software development lifecycle
• Awareness of AI/ML security and responsible-AI considerations, including model risk, data privacy, secure handling of sensitive data, and threat modeling for AI-enabled products.
• Understanding of vulnerability management, incident response, and secure SDLC practices; ability to coordinate cross-functional security remediation efforts.
• Relevant security certifications such as CISSP, CCSP, CompTIA Security+, or CISM are a plus.