Director, Network Automation Engineering

Reporting to the Vice President, Global Network Engineering and Operations (GNEO), the Director, Network Automation Engineering is responsible for defining and driving the strategic implementation of advanced automation, real-time observability platforms, AI/ML solutions, and integrated network tooling. This leader ensures operational excellence across all network service domains and fosters innovation that aligns with Disney’s enterprise technology and business goals. This executive will enable networking innovation, scalability, security, and reliability through a robust and forward-thinking network reliability engineering mindset and will assist in driving the transformation of Disney’s Global Network Engineering & Operations organization into a NetDevOps-driven model.

Responsibilities:

Strategic & Technical Leadership:

• Develop and execute a unified vision for automation, orchestration, observability, and AI/ML capabilities within the network domain.

• Lead transformation efforts to shift to Infrastructure-as-Code (IaC), CI/CD pipelines, and cloud-native operations.

• Drive architectural convergence and platform integration across SASE, SD-WAN, and NetDevOps toolsets.

• Partner with architecture, platforms, and operations teams to ensure consistent, scalable network services.

Automation, Orchestration & Observability Delivery:

• Oversee the delivery of automation platforms, observability tools, and performance monitoring frameworks.

• Deploy real-time telemetry and distributed tracing to support intelligent decision making and predictive analytics.

• Introduce self-service workflows, APIs, and reusable modules for infrastructure provisioning and change management.

• Embed AI/ML into anomaly detection and capacity planning capabilities across network services.

Service Excellence & Optimization:

• Ensure service reliability, operational uptime, and continuous performance improvement through automated workflows.

• Establish operational KPIs and develop dashboards for executive and technical consumption.

• Coordinate incident response, root cause analysis, and proactive issue detection.

• Standardize tools and templates to drive consistency, reduce manual errors, and improve MTTR.

Team Development & Engineering Culture:

• Inspire, grow, and lead high-performing teams focused on software engineering, NetDevOps, and network reliability.

• Foster a culture of experimentation, learning, automation-first thinking, and cross-functional collaboration.

• Upskill engineering teams in Python, Ansible, Terraform, and observability platforms like Grafana, Prometheus, etc.

• Oversee workforce planning, mentoring, and succession strategies for key engineering talent.

Business Partnership & Collaboration:

• Engage with stakeholders, segment executives, and enterprise architects to ensure alignment with company objectives.

• Represent GNEO in forums, driving technology roadmaps, tooling investments, and infrastructure innovation.

• Manage vendors and service providers, including SLAs, tool integrations, and support escalations.

• Support strategic initiatives through site visits, leadership engagement, and executive presentations (travel up to 20%).

Qualifications:

• 10+ years of progressive leadership in network engineering, automation, observability, or SRE roles.

• Demonstrated success implementing Infrastructure-as-Code, orchestration frameworks, and CI/CD pipelines.

• Hands-on experience with technologies such as Python, Ansible, Terraform, Grafana, Prometheus, and telemetry standards (OpenTelemetry).

• Proven ability to lead NetDevOps or software-defined transformation initiatives across large enterprise environments.

• Strong business acumen, communication skills, and cross-functional stakeholder engagement experience.

• Fluency in automation frameworks and observability best practices, including service mesh and distributed tracing.

Preferred Qualifications:

• Master’s degree in IT Systems, Engineering, Business Administration (MBA) or in any other discipline.

• Certifications such as CCNP, ITIL, Kubernetes, PMP, Python, or AI/ML platforms.

Education:

Bachelor’s degree in Computer Science, Engineering, Information Technology, or related field.

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