AI Software Development Manager

• Pay or shift range: $144,500 CAD to $170,000 CAD. The estimated range is the budgeted amount for this position. Final offers are based on various factors, including skill set, experience, location, qualifications and other job-related reasons.

When data is complex and the mission is critical, law enforcement, intelligence, and security organizations around the world trust JSI. Our 4

Sight platform fuses disparate data sources — communications, location, OSINT, financial activity, and more — to expand awareness, surface patterns, and simplify data complexity for the teams that rely on it. AI and machine learning sit at the center of how 4

Sight does that work, and the quality of those capabilities has direct, real‑world consequences for the investigations and operations they support.

We are hiring an experienced Engineering Manager to lead two agile AI/ML teams (~10 engineers total) building production AI capabilities inside our 4

Sight platform. You will be accountable for delivery, engineering quality, and team performance, and you will help shape the technical direction in partnership with senior engineering leadership and architects.

This is a hands‑on technical leadership role. We want a manager who still reads code, engages in design discussions, and exercises real judgment on architecture and trade‑offs alongside their teams. You will operate in a fast‑moving AI environment where priorities shift, ambiguity is the norm, and the bar for production reliability is high.

Before you apply: this role requires eligibility for a Government of Canada Top Secret security clearance. The position is based in Kanata, Ontario, with at least two days per week of in‑office collaboration.

Leadership & Team Management

• Lead, manage, and mentor two agile teams of software developers, data scientists, and AI engineers (~10 direct reports)
• Hire, develop, and retain high‑performing engineering talent
• Conduct performance management, career development, and coaching
• Foster a culture of accountability, collaboration, and continuous improvement
• Set clear expectations and ensure alignment with team and organizational goals
• Act as an escalation point for team‑level challenges and cross‑team dependencies

Delivery & Execution

• Accountable for the delivery outcomes, engineering quality, and performance of both teams
• Ensure predictable, sustainable delivery practices aligned with business objectives
• Manage scope, risks, and dependencies across concurrent initiatives
• Partner with Product Management to translate business goals into executable plans
• Ensure high‑quality releases and effective handling of production issues and support needs
• Evolve agile practices, testing discipline, and release processes to improve delivery outcomes and team effectiveness over time

Technical Leadership

• Set and execute the technical direction for your product area
• Maintain sufficient technical depth to guide design decisions and review critical architecture
• Partner with senior engineers to ensure sound technical execution and maintainability
• Identify and manage technical debt, balancing short‑term delivery with long‑term system health

AI/ML Execution

• Lead delivery of AI/ML capabilities across investigative use cases — entity resolution, link analysis, anomaly and pattern detection, NLP on unstructured communications, and similar problems against large, heterogeneous datasets
• Drive the path from experimentation to production: dataset curation, model evaluation against operational metrics, deployment, monitoring for drift, and retraining cycles
• Hold a high bar for model validation in a domain where false positives and false negatives both have real consequences for investigations and the people involved
• Partner with data and platform teams on the infrastructure that makes production ML reliable — feature stores, evaluation harnesses, observability, and lifecycle tooling
• Champion responsible‑AI practices: bias review, explainability where it matters, auditability, and clear human‑in‑the‑loop boundaries

• 10+ years of software engineering experience, including 5+ years managing engineering teams with direct delivery…