Engineering Manager, AI Engineering

Magnet Forensics

Engineering Manager leading AI engineering projects at Magnet Forensics. Overseeing team development, technical execution, and operational excellence in digital investigative software.

Posted 6/3/2026full-timeGothenburg • 🇸🇪 SwedenMid-LevelSeniorWebsite

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

3+ years managing or leading teams of engineers, with a track record of building healthy teams, delivering results, and coaching people through growth (regardless of title);
Hands-on experience building applied AI/ML systems. Enough 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 other people's growth, give direct and useful feedback, and have coached Senior and Staff-level engineers; people who don't need hand-holding but benefit from thoughtful partnership;
Sound technical judgment. You can navigate complex decisions, weigh trade-offs, and help teams move toward adaptable, maintainable solutions, even when the right answer isn't obvious;
Strong cross-functional instincts. You communicate clearly with engineers, PMs, UX, and leadership, and understand that your job is to make the whole system work, not just to deliver features;
Experience working effectively across distributed teams. You understand that "remote" and "distributed" are different things, and know how to build cohesion when people aren't in the same room;
Familiarity with AI-assisted development tools and a perspective on how to effectively integrate them into engineering workflows and team practices;
Bachelor's degree in Computer Science, Computer Engineering, or a related technical field; or equivalent practical experience.

Benefits

Comp & perks

Generous time off policies
Competitive compensation
Volunteer opportunities
Reward and recognition programs
Employee committees & resource groups
Healthcare and retirement benefits

ATS Keywords

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Hard Skills & Tools

AI systemsML systemstechnical judgmentadaptable solutionsmaintainable solutionscoachingproject scopingrisk assessmenttrade-off analysisengineering workflows

Soft Skills

coaching mindsetclear communicationcross-functional collaborationteam buildingfeedback deliveryproblem-solvingtrust buildingoperational excellencedecision makingexperimentation