Director, Software Engineering

Director of Software Engineering

Role Overview

The Director of Software Engineering is responsible for end-to-end digital delivery and reliability, overseeing software engineering, DevOps and platform operations, quality engineering, user experience design, and business analysis. This role ensures that business intent is translated into high-quality, user-centered digital solutions that are designed, built, tested, released, and operated with strong reliability, security, and performance.

A core expectation of this role is to increase automation and efficiency across the delivery lifecycle, including the responsible use of generative AI and intelligent automation to augment business analysis, design, development, testing, and operational practices. The Director balances customer experience, delivery speed, technical sustainability, and operational stability while enabling teams to focus on higher-value, human-centered work.

This role is hybrid. We are in the office every other week, Tuesdays – Thursdays. During December, June – August we are in the office one week a month for three consecutive days (Tuesday – Thursday).

Key Responsibilities

Leadership & Strategy Execution

• Translate business and digital strategy into clear delivery priorities, roadmaps, and execution plans.
• Ensure alignment between business intent, user experience, technical execution, quality, and operational outcomes.
• Partner with Product, Digital, Marketing, and business leaders to prioritize initiatives and manage trade-offs.
• Serve as the escalation point for cross-functional delivery, automation, and operational risks.
• Own delivery outcomes for customer-facing digital platforms.

Software Engineering Leadership

• Lead engineering teams to deliver scalable, secure, and maintainable software solutions.
• Establish and enforce engineering standards, architectural guardrails, and modern development practices.
• Promote automation-first development practices to reduce manual effort and rework.
• Leverage generative AI–assisted tools to improve developer productivity, code quality, documentation, and refactoring—within defined security and quality guardrails.
• Ensure strong collaboration between engineering, UX, QA, BA, and DevOps to accelerate delivery.

DevOps & Platform Operations Leadership

• Own accountability for CI/CD pipelines, deployment automation, environments, and release practices.
• Ensure platforms meet standards for reliability, availability, performance, scalability, and security.
• Promote shared ownership of production outcomes across delivery teams.
• Leverage automation and AI-enabled tooling to reduce operational toil, improve release readiness, and surface risks earlier.
• Use operational metrics (availability, incident trends, deployment frequency) to drive continuous improvement.
• Partner with Infrastructure and Security teams to ensure operability and compliance.

Business Analysis & Requirements Leadership

• Ensure business needs are clearly articulated, prioritized, and translated into actionable requirements and acceptance criteria.
• Establish standards for requirements quality, clarity, and traceability.
• Leverage generative AI and automation to assist with requirements drafting, analysis, validation, and documentation—freeing analysts to focus on stakeholder engagement and decision-making.
• Partner with Product and business stakeholders to focus analysis on outcomes and value, not documentation volume.
• Ensure business analysis supports discovery, solutioning, and delivery throughout the lifecycle.

User Experience & Design Leadership

• Own accountability for the quality, consistency, and accessibility of user experience across digital platforms.
• Ensure UX/UI design is grounded in user needs, brand standards, and accessibility best practices.
• Promote early design involvement in discovery and solutioning.
• Leverage AI-assisted design and research tools to accelerate ideation, prototyping, usability analysis, and design iteration—while preserving human judgment and creativity.
• Balance usability, feasibility, performance, and delivery constraints in collaboration with engineering and DevOps.

Quality Engineering & Assurance Leadership

• Own the overall quality strategy, including test automation, performance testing, security testing, and release readiness.
• Drive increased use of automated testing across unit, integration, and end-to-end levels.
• Leverage AI- and generative AI–assisted tools to accelerate test creation, maintenance, and defect detection.
• Reduce reliance on manual regression testing through automation and intelligent tooling.
• Ensure quality is embedded throughout the delivery lifecycle rather than treated as a downstream activity.
• Use quality and automation metrics to drive continuous improvement and release confidence.

Delivery & Operational Excellence

• Own Agile delivery health, release planning, dependency management, and risk mitigation.
• Establish and monitor KPIs related to delivery predictability, quality, automation coverage, and operational performance.
• Balance delivery speed with operational risk and long-term sustainability.
• Identify and implement opportunities to use automation and AI to improve efficiency, reduce rework, and free capacity for innovation and roadmap execution.

People & Talent Leadership

• Lead multidisciplinary teams including engineers, DevOps professionals, QA, UX/UI designers, and business analysts.
• Recruit, develop, and retain high-performing digital delivery talent.
• Coach functional and technical leaders to operate with strong decision-making authority and accountability.
• Build a culture that embraces automation, continuous learning, and responsible AI use.
• Develop future leaders across engineering, DevOps, quality, design, and analysis disciplines.

Skills & Experience

• Proven experience leading end-to-end digital delivery organizations, including engineering and DevOps.
• Demonstrated success increasing test automation and delivery automation maturity across teams.
• Working knowledge of generative AI and AI-assisted tools applied to software development, testing, design, or analysis.
• Ability to evaluate emerging automation and AI tools and integrate them responsibly into delivery practices.
• Strong understanding of modern software development, CI/CD, cloud platforms, observability, and automation.
• Experience operating customer-facing digital platforms with high reliability expectations.
• Strong business acumen and ability to balance experience, speed, quality, cost, and reliability.
• Excellent communication and stakeholder management skills.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Design, or a related field, or equivalent practical experience.
• 10+ years of experience in software engineering, DevOps, or digital delivery roles.
• 7+ years of leadership experience managing senior professionals and cross-functional teams.
• Experience operating in complex, customer-facing digital environments.
• Understanding of Customer Journey and data to collect and monitor
• 5+ years’ experience working in an e-com business
• Preferred: 3+ years working in a subscription business