Own end-to-end engineering execution across development, architecture, platform, and QA
Ensure consistent delivery of high-quality software that meets scope, timeline, and budget commitments
Establish clear engineering goals, metrics, and accountability across teams
Drive predictable, scalable delivery through strong planning, estimation, and execution practices
Manage vendor selection and delivery when appropriate
Set and uphold engineering standards, best practices, and development methodologies
Ensure a strong, secure, scalable, and maintainable technology foundation
Provide architectural oversight and technical leadership across systems and platforms
Guide technology choices and leverage modern, leading-edge technologies where they create real business value
Evaluate, adopt, and integrate AI and machine learning technologies where they create meaningful product differentiation or operational efficiency
Balance innovation with pragmatism and operational stability
Define and own the company’s AI strategy, aligned with business objectives, product roadmap, and long-term technology vision
Identify, prioritize, and oversee AI use cases across product development, engineering operations, and internal business functions
Lead the adoption of AI tools and platforms to improve engineering velocity, software quality, and overall technology productivity
Establish standards and governance for responsible AI use, including security, privacy, compliance, and ethical considerations
Partner with Product, Data, and Business leaders to translate AI capabilities into measurable business outcomes
Ensure quality is built into the development lifecycle through strong QA, automation, and testing practices
Drive high standards for reliability, performance, security, and operational excellence
Lead, mentor, and scale a large, diverse global engineering organization
Attract, hire, develop, and retain top engineering talent at all levels
Build a strong engineering culture centered on ownership, accountability, collaboration, and continuous learning
Foster an AI-literate engineering culture through training, enablement, and best practices that enhance—not replace—human judgment and creativity
Develop future engineering leaders and succession plans
Partner closely with Product, Experience, and other business leaders to align engineering execution with product vision and business goals
Translate product strategy into clear technical plans and delivery roadmaps
Communicate clearly and effectively with executive leadership and stakeholders

Requirements

15+ years of experience in software engineering, with significant experience leading large engineering organizations
Proven track record of delivering complex software products at scale, on time, on budget, and with high quality
Deep technical background with the ability to engage in architecture, design, and technical decision-making
Strong experience establishing engineering standards, best practices, and scalable development processes
Demonstrated success hiring, developing, and retaining high-performing engineering teams including offshore
Experience operating in fast-paced, high-growth environments
Excellent leadership, communication, and stakeholder management skills
Experience modernizing platforms or building large-scale distributed systems
Background in cloud-native architectures, modern development stacks, and DevOps practices (we’re a Microsoft shop)
Experience working closely with product-led organizations
Prior experience as VP or SVP of Engineering or equivalent leadership role

Benefits

insurance offerings such as medical, dental, vision, retirement savings programs, among others, starting day one of employment
annual discretionary bonus plan
incentive or sales bonus plan
other forms of additional compensation

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

software engineeringarchitecturedesigntechnical decision-makingengineering standardsdevelopment processescloud-native architectureslarge-scale distributed systemsDevOps practicesAI and machine learning technologies

Soft Skills

leadershipcommunicationstakeholder managementmentoringcollaborationaccountabilitycontinuous learninginnovationpragmatismorganizational development