Vice President, Production Engineering

Role

Production Engineering applies software engineering principles to production systems, shifting operations from reactive, human-driven intervention to proactive, software-driven reliability and scale.

The Vice President / Senior Vice President of Production Engineering is the senior executive accountable for the reliability, performance, scalability, and security of NICE’s global, AI-first platforms.

The leader who fills this role is the owner of end-to-end production environments across NICE’s Cloud, Telecom, and Datacenter platforms, accountable for the operational outcomes of those platforms.

The selected leader will drive the transformation of a diverse, operations-heavy organization into a modern, AI-first function.

Responsibilities

Production Engineering Transformation

• Lead the evolution of an organization that includes software engineers, systems engineers, network engineers, telecom engineers, database administrators, application operations, DevOps, SRE, and NOC personnel into a cohesive Production Engineering function.

• Shift the organization from ticket-driven, reactive operations toward software-first, automated systems that proactively ensure reliability and scale.

• Define future-state roles, skill sets, and career paths aligned with Production Engineering and AI-first platform needs.

• Drive up-skilling, re-skilling, and selective hiring to build modern production engineering capabilities.

Platform Operations

• Own the engineering and operation of global cloud infrastructure, telecom platforms, and datacenter environments.

• Ensure production systems meet defined availability, performance, scalability, security, and cost targets.

• Establish and enforce production readiness standards across all platform services.

• Own operational governance for capacity planning, resilience, disaster recovery, and business continuity.

Production Engineering Discipline

• Establish Production Engineering as a core engineering discipline embedded with Product Engineering teams.

• Drive adoption of software-first operational practices including automated recovery, infrastructure as code, synthetic testing, and observability.

• Ensure reliability, scalability, performance, and security are treated as first-class design requirements, not post-release concerns.

• Influence architecture and delivery decisions early to prevent systemic production risk.

Reliability, Observability & Incident Leadership

• Define and maintain service level indicators (SLIs) and service-level objectives (SLOs), error budgets, and reliability metrics across the platform.

• Own observability strategy, including monitoring, alerting, logs, metrics, tracing, and capacity signals.

• Lead global incident management, escalation, and executive-level response during major platform events.

• Ensure incidents drive learning and systemic improvement rather than repeat failures or hero-driven response.

Automation, AI & Platform Enablement

• Drive the adoption of AI-assisted operations, automation, and agent-based workflows across production environments.

• Leverage AI to improve detection, diagnosis, remediation, and capacity forecasting while maintaining appropriate human-in-the-loop controls.

• Own CI/CD pipelines, deployment automation, and infrastructure-as-code practices.

• Reduce operational toil and manual intervention through automation and self-service platforms.

Cross-Functional Partnership

• Partner with Product Engineering to align platform capabilities with product delivery commitments.

• Partner with Customer Support to strengthen feedback loops from customer experience into engineering action.

• Partner with Security to ensure platforms are secure by design and compliant by default.

• Act as a senior operational leader during customer-impacting events and executive escalations.

Organization & Talent Leadership

• Lead, scale, and grow global teams within Production Engineering.

• Build strong leadership layers and develop senior technical leaders.

• Foster a culture of ownership, bias for action, operational excellence, and continuous improvement.

• Attract, retain, and develop world-class production engineers capable of operating AI-first platforms at scale.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related technical field

• 15+ years of engineering leadership experience operating large-scale, distributed platforms.

• 8+ years leading senior engineering or operations organizations spanning infrastructure, platform, or production environments.

• Proven experience leading organizational and skill transformation within engineering or operations teams.

• Strong background in cloud infrastructure, distributed systems, networking, and runtime platforms.

• Demonstrated ability to establish engineering standards and influence architecture across organizations.

• Experience partnering with Product, Security, and Support leaders in complex environments.

Preferred

• Experience operating AI-enabled or data-intensive platforms in production.

• Experience modernizing legacy operations or NOC-based organizations.

• Background in Production Engineering or SRE organizations at scale.

• Experience operating in regulated, sovereign, or enterprise customer environments.