Senior Director, Engineering | Retail Analytics / CPG / Market Intelligence
$148,900–$180,000 year
RemoteCanada
EXPIREDCanadaRemoteFull Time$148,900–$180,000 yearSenior LevelEnterprise
Full TimeSenior LevelEnterprise
Job Summary
Lead the AI-first transformation of customer-facing SaaS product engineering capabilities, driving evolution from mature SaaS models to AI-enabled innovation in decision support and automation. Define technical direction and system design for large-scale distributed platforms, guiding modernization of data-intensive services while balancing new capability development with technical debt reduction. Ensure production excellence across reliability, security, and observability, adopting GenAI practices to improve developer productivity and software quality. Mentor Directors, Senior Managers, and Principal Engineers in a globally distributed, matrixed environment, fostering a culture of constructive challenge and ownership.
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, or a related technical field
- 15+ years of progressive technology and software engineering leadership experience
- Proven experience leading and developing senior engineering leaders and technical leaders, including Directors, Senior Managers, Principal Engineers, or equivalent roles
- Demonstrated success leading engineering for customer-facing enterprise SaaS products, data-intensive platforms, analytics products, or comparable large-scale commercial software platforms
- Experience driving engineering transformation across mature SaaS environments, including modernization, technical debt reduction, quality improvement, and delivery acceleration
- Current experience leading AI-enabled product capability development within enterprise SaaS or comparable commercial software environments
- Experience applying GenAI tools and AI-assisted practices within engineering workflows to improve software delivery, quality, developer productivity, or modernization outcomes
- Experience leading globally distributed engineering teams in a matrixed organization
- Deep software engineering background with strong system design, distributed systems, and architecture experience
- Strong understanding of cloud-native architecture, scalable platform design, data-intensive systems, API design, integration patterns, performance optimization, reliability engineering, and enterprise architecture principles
- Prior hands-on engineering experience and leadership familiarity with technologies used by modern SaaS teams, including Java, Python, Angular, Azure cloud services, and AI/GenAI technologies and frameworks
- Ability to evaluate architectural options, challenge design assumptions, and guide technical tradeoffs across speed, quality, scalability, cost, security, maintainability, and customer impact
- Strong understanding of modern software development practices, including Agile delivery, CI/CD, automated testing, observability, secure engineering practices, and production operations
- Transformative mindset with the ability to move teams from established SaaS operating models toward AI-first product and engineering approaches
- Ability to challenge the status quo constructively, challenge self and teams to improve, and bring others along through influence, clarity, and technical credibility
- Strong executive presence, stakeholder management, and communication skills across technical and non-technical audiences
- High accountability for engineering outcomes, customer impact, and business-aligned execution
- Ability to operate effectively in ambiguity, make decisions with incomplete information, and create alignment across competing priorities
- Strong coaching and talent development skills, with a track record of building high-performing engineering leadership teams
Desired Qualifications
- Experience leading AI-driven product transformation initiatives that created measurable customer value or commercial impact
- Experience with modern AI/GenAI application patterns, orchestration frameworks, model integration, retrieval-augmented generation, agentic workflows, or AI-enabled analytics experiences
- Experience in retail, CPG, consumer measurement, market intelligence, data analytics, or adjacent data-rich enterprise domains
- Background working in product-led technology organizations with close partnership across Product Management, Design, Architecture, Data Science, Security, and Business stakeholders
- Experience improving engineering operating models through metrics, platform thinking, engineering productivity practices, and production excellence
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.