Engineering Manager, Enterprise

Responsibilities

• Own end-to-end delivery of core product initiatives, from technical design through execution and iteration, while directly managing a high-performing fullstack engineering team.
• Set technical direction for large-scale, AI-powered systems, including:
  • Retrieval over petabyte-scale document collections.
  • Product interfaces that enable organizations to collaborate with AI.
  • Long-horizon (1000+ step) planning agents for mission-critical workflows.
  • Government-grade security for highly sensitive data.
  • Evaluation of LLMs across a 10k+ leaf taxonomy of tasks.
  • Internet-scale data collection across 50+ jurisdictions.
• Translate product vision into architecture, making pragmatic tradeoffs that balance speed, quality, and long-term scalability.
• Contribute to design, code, and architecture reviews, and dive into implementation to unblock the team or tackle difficult problems.
• Build and grow the team by hiring engineers, setting technical and behavioral standards, and investing in mentorship and career development.
• Partner with Product, Design, and AI to identify opportunities and ship intuitive, detail-oriented user experiences.
• Establish an engineering culture centered on simplicity, ownership, craftsmanship, and continuous improvement.
• Align execution with company goals and product strategy.

Requirements

• 6+ years of experience as a product-focused fullstack or backend software engineer, post-BS/MS, with a history of shipping products to users.
• 2+ years of experience leading engineers, with ownership over delivery and team health.
• Ability to design and operate backend platforms supporting multiple product lines at scale.
• Strong experience with modern frontend frameworks such as React or backend systems such as Python, Node, or Go.
• Excellent technical judgment and ability to balance speed, investment, and simplicity.
• Strong product instinct and attention to detail, with a track record of building intuitive, high-quality user experiences.
• Success building, motivating, and retaining high-performing teams in high-growth environments.
• Solid computer science fundamentals and strong programming skills.
• Grit and an ownership mindset, with comfort operating in ambiguity and taking responsibility for outcomes.

Nice-to-haves

• Experience with AI-powered applications, large-scale data systems, LLM evaluation, or complex internal platforms.

Compensation and Benefits

• Hybrid working arrangement: 3 days in the Toronto office and 2 days working from home.
• Relocation assistance for new employees.
• The role may be eligible for a bonus plan or role-specific commission/bonus and annual refresh equity grants.
• Compensation offers are based on factors including geography, experience, skills, job duties, and business need.