Engineering Manager, AI Engineering

Role Overview

We are looking for an Engineering Manager to build, develop, and partner with a growing team of 5-10 ML Engineers working on AI systems that power our digital forensics capabilities. You'll be responsible for hiring, coaching, career development, and performance; raising the bar on AI/ML craft by shaping standards, developing engineers, and building a strong community of practice across the team.

Distributed across Canada and Sweden, our MLEs work in cross-functional groups alongside Software Engineers and SDETs, and are organized around missions like Search and Enrichment rather than by technical discipline. As part of the AI Engineering leadership team, you'll work alongside peers to build cohesion across those groups, partner with Tech Leads to shape how we approach difficult technical problems, and collaborate with Product and UX to make sure the team is solving the right problems for our users.

From building AI that investigators can trust to turn months of case work into days, to figuring out what  good  looks like when users are searching for a needle in a haystack they ve never seen before, our team works on challenging and meaningful problems. If these are the kinds of problems that interest you, then you will feel at home on this team!

• Drive operational excellence. Stay accountable for what the team ships, and continuously improve how we work by building frameworks for efficient, high-quality delivery. Protect team autonomy by bringing clarity and keeping decision making complexity low.
• Guide technical execution. Stay close enough to the technical work to ask sharp questions, spot risks, and help the team weigh trade-offs. Partner with Tech Leads to ensure complex initiatives have the right direction, and that our systems are adaptable and aligned with long-term goals.
• Coach and grow engineers on the team. Help them scope ambiguous projects, navigate tough technical trade-offs, and prepare for high-stakes conversations. Create opportunities for them to take ownership and expand their impact, and support them through clear, actionable feedback.
• Foster a culture of experimentation. Create an environment where the team can safely share and test ideas, measure results, and learn quickly from each other and our data to keep pace in a rapidly evolving space.
• Lead with context and collaboration. Work across Product, UX, and engineering leadership to align roadmap goals with team capacity and ensure the team is solving the right problems for our users.
• Nurture a high-performing, distributed team. Evolve our processes and communication patterns to enhance our distributed collaboration while maintaining a high level of trust within the team. Leverage our time zone coverage in Canada (ET/MT) and Sweden (CET) as an advantage, not a constraint to overcome.
• Drive thoughtful AI-assisted development practices. Figure out where AI development tools accelerate the team versus where they create risk, and raise our standards accordingly. Cut through the noise to determine what adds real value vs. what is only hype.

• 3+ years managing or leading teams of engineers, with a track record of building healthy teams, delivering results, and coaching people through growth.
• Hands-on experience building applied AI/ML systems. Ability to understand what good looks like, evaluate technical judgment, and have credible conversations on technical topics with the team.
• A genuine coaching mindset. You find satisfaction in others  growth, give direct and useful feedback, and have coached Senior and Staff-level engineers.
• Sound technical judgment. You can navigate complex decisions, weigh trade-offs, and help teams move toward adaptable, maintainable solutions.
• Strong cross-functional instincts. You communicate clearly with engineers, product managers, UX, and leadership, and understand that your job is to make the whole system work, not just deliver features.
• Experience working effectively across distributed teams. You understand remote work and know how to build cohesion when people aren t in the same room.
• Familiarity with AI-assisted development tools and how to integrate them into engineering workflows and team practices.
• Bachelor s degree in Computer Science, Computer Engineering, or a related field; or equivalent practical experience.

• Experience in high-stakes domains (security, healthcare, legal) where correctness matters.
• Experience with AI/ML in constrained deployment models (on-prem, edge, air-gapped).
• Experience building and operating scalable, distributed systems.
• Familiarity with MLOps tooling (e.g., experiment tracking, model versioning, CI/CD for ML).

The compensation range is for the primary location for which the job is posted. Actual compensation may vary by location and factors such as qualifications, experience, knowledge, and skills. If applying outside the primary location and selected for an interview, the Talent Acquisition Partner can share more…