Position OverviewThe Vice President, Software Delivery is responsible for enterprise software delivery execution, platform modernization, and engineering operating model transformation across the Business Unit. This leader owns delivery outcomes across squads, drives platform consolidation strategy, establishes engineering governance standards, and ensures alignment between business priorities, enterprise architecture, AI initiatives, and technology execution.
The Vice President serves as the senior technical delivery leader for the organization, overseeing Business Unit delivery leadership while partnering closely with Product, Infrastructure, DevOps, Database, Security, AI, PMO, and Operations leadership. This role will guide the transition from fragmented delivery models into standardized, platform-oriented engineering capabilities that improve scalability, reduce duplication, accelerate delivery velocity, and strengthen operational reliability.
The ideal candidate has demonstrated experience deploying AI-enabled engineering practices and tools to maximize engineering productivity and efficiency while expanding quality, automation, and operational reliability across the software delivery lifecycle.
What You Will OwnThis role owns enterprise software delivery performance and KPI accountability across Business Units, including delivery predictability, quality, operational stability, production health, and execution against strategic roadmap commitments. The Vice President will also own the technical leadership system centered on Tech Lead accountability, embedded architectural ownership, consistent KPI governance, disciplined PSR execution, and PMO-supported cross-department initiative delivery.
Essential Responsibilities- Collaborate with architecture and delivery peers on enterprise vision and strategy for Software Delivery across all Business Units.
- Own delivery KPIs for predictability, quality, operational stability, and production health.
- Lead platform consolidation and modernization into reusable services, APIs, and common engineering patterns.
- Establish engineering standards for CI/CD, code review, automated testing, security scanning, release readiness, rollback, observability, and incident learning.
- Drive measurable improvement in deployment frequency, lead time, defect escape rate, change failure rate, incident trends, and delivery predictability.
- Ensure enterprise architecture standards and AI directives are adopted across products and squads.
- Partner with Product, Infrastructure, DevOps, Database, Security, AI, PMO, Operations, QA COE, and Support to align enterprise initiatives with delivery execution.
- Oversee Daily Management, KPI reviews, release readiness, production health reviews, and PSR execution across Business Units.
- Drive AI-enabled engineering capabilities that improve developer productivity, test automation, defect reduction, documentation, incident analysis, and operational insight.
- Establish responsible AI usage standards that balance productivity with security, compliance, maintainability, and quality.
- Represent Software Delivery in executive customer, partner, and stakeholder discussions.
- Build and coach high-performing delivery leadership teams, including BU leaders, Domain Software Managers, and Tech Leads.
- Oversee CapEx and OpEx alignment, resource planning, and platform/tooling investments tied to delivery velocity and stability.
Qualifications- Bachelor degree in Computer Science, Engineering, or equivalent experience.
- 12+ years of software engineering leadership experience, including 7+ years leading multiple teams or Business Units.
- Proven success leading platform transformation, modernization, consolidation, and governance across legacy and modern systems.
- Experience implementing scalable engineering governance models, Agile/Lean delivery practices, and measurable flow and quality improvements.
- Demonstrated experience deploying AI-enabled engineering practices, developer productivity tooling, or intelligent automation within software delivery organizations.
- Strong executive communication, stakeholder management, and organizational leadership capability.
- Successful completion of the Nlets fingerprinting background assessment.
Technical Background- Experience across enterprise software delivery, platform ecosystems, APIs, microservices, cloud platforms, containers, CI/CD, observability, and reliability engineering.
- Ability to evaluate platform strategy, delivery tradeoffs, architectural direction, modernization paths, AI-enabled engineering practices, and operational risk.
- Familiarity with SaaS or large-scale digital platforms, internal developer platforms, distributed systems, and legacy modernization.
Leadership Competencies- Strategic Mindset: Aligns delivery, platform consolidation, modernization, AI adoption, and business growth.
- Ensures Accountability: Owns enterprise delivery outcomes and creates clear accountability across BU leaders, Domain Software Managers, Tech Leads, Scrum Masters, PMO, QA COE, and Support.
- Builds Effective Teams: Develops strong delivery leaders and strengthens succession planning, coaching, ownership, and continuous learning.
- Customer Focus: Ensures delivery models improve customer outcomes, reliability, operational excellence, and predictable execution.
- Cultivates Innovation: Advances modern engineering, automation, platform capabilities, and AI-enabled productivity while maintaining governance discipline.
- Decision Quality: Balances speed, quality, reliability, security, scalability, maintainability, and business value.
- Communicates Effectively: Aligns Product, Engineering, Infrastructure, DevOps, Database, Security, AI, PMO, Operations, and executive stakeholders.
- Complex Ecosystem Delivery: Orchestrates execution across product, platform, infrastructure, quality, support, and operations domains.
Success in the First 6 Months- Establish enterprise delivery governance, KPI operating model, decision rights, Tech Lead accountability, and PMO engagement rules.
- Define platform consolidation roadmap, modernization priorities, shared service opportunities, and legacy deprecation approach.
- Improve delivery predictability and operational KPI performance quarter over quarter.
- Standardize release readiness and production health reviews across Business Units.
- Strengthen alignment with Infrastructure, DevOps, Database, Security, AI, Product, and PMO leadership.
- Launch initial AI-enabled engineering productivity initiatives with measurable improvements in efficiency, quality, automation, or operational effectiveness.
