StackAdapt

StackAdapt

Director, Engineering

Canada; United States · Director

Sponsorship not specifiedDetected 28 days ago
Distributed SystemsBackend DevelopmentSite Reliability EngineeringData ScienceStakeholder ManagementPerformance MarketingExcelOnboardingCustomer SupportSignal ProcessingLeadershipCommunicationCollaboration

About the role

  • StackAdapt is the leading technology company that empowers marketers to reach, engage, and convert audiences with precision.
  • The most forward-thinking marketers choose StackAdapt to orchestrate high-impact campaigns across programmatic advertising and marketing channels.
  • You will work with large-scale distributed systems, real-time data processing, user identity, integrations, and activation services that are critical to StackAdapt's success.

Responsibilities

  • Lead, mentor, and grow multiple engineering managers and senior engineers, fostering a culture of high performance, ownership, and continuous improvement.
  • Drive technical decision-making and establish standards for architecture, scalability, reliability, and operational excellence.
  • Help develop future engineering leaders and support organizational growth as the company continues to scale.
  • Oversee the design and evolution of backend systems supporting user identity, integrations, activation, and data processing capabilities.
  • Ensure systems support high-scale, low-latency, and highly available workloads.
  • Partner with Infrastructure, SRE, Product, and Data teams to improve reliability, observability, and operational efficiency.
  • Champion best practices in software development, distributed systems design, and engineering excellence.
  • Build strong partnerships across the organization and represent engineering in strategic initiatives.
  • With 465 billion automated optimizations per second, the AI-powered StackAdapt Marketing Platform seamlessly connects brand and performance marketing to drive measurable results across the entire customer journey.
  • As a Director, Engineering at StackAdapt, you will be directly involved in leading teams responsible for building and evolving the backend systems that power our advertising platform.

Requirements

  • 15+ years of professional software engineering experience, with 8+ years in engineering leadership roles.
  • Proven experience leading multiple engineering teams through managers in a high-scale SaaS, infrastructure, or data-intensive environment.
  • Experience in AdTech, MarTech, identity platforms, data platforms, or real-time systems is a strong asset but not required.
  • Strong technical background in distributed systems, cloud-native architectures, APIs, and large-scale backend services.
  • Track record of developing engineering leaders and building high-performing teams.
  • Excellent communication and stakeholder management skills.
  • StackAdapter's Enjoy:
  • Highly competitive salary
  • Retirement/ 401K/ Pension Savings globally
  • Competitive Paid time off packages including birthday's off!
  • Access to a comprehensive mental health care program
  • Health benefits from day one of employment
  • Work from home reimbursements

Compensation

  • Highly competitive salary

Benefits

  • Coverage and support of personal development initiatives (conferences, courses, books etc)
  • Access to StackAdapt programmatic courses and certifications to support continuous learning
  • An awesome parental leave program
  • Own the vision, strategy, and roadmap for a large backend engineering organization, aligning engineering investments with business and product goals.
  • Balance short-term delivery needs with long-term system health and scalability.
  • You will have the opportunity to work in a diverse and flexible culture with dedicated career paths to help you succeed.

Company info

  • We are looking for a Director, Engineering to lead teams responsible for building and scaling backend services across user data, integrations, and activation domains.

This listing is sourced directly from StackAdapt's careers page and normalized into a canonical job model.