Senior Engineering Manager

About this role

Description General Information: Job Title: Senior Engineering Manager Location: Toronto, ON (Onsite/Hybrid) Job Type: Full-Time Reporting Line: Senior Vice President, Architecture Salary Range: CAD 150k–170k CAD per year (negotiable)

About Fulfillment IQ (FIQ): Fulfillment IQ is a supply chain engineering and transformation company that helps brands, retailers, and 3PLs design, build, and scale high-performance logistics operations. We work at the intersection of strategy, operations, and technology where we solve complex, real-world problems across warehouse design, automation, order management, transportation, and end-to-end supply chain execution.

Our teams combine deep domain expertise with strong technical capability, delivering outcomes through consulting, systems implementation, and proprietary platforms that accelerate time-to-value and reduce delivery risk.

If you enjoy working in complex environments, partnering closely with clients, and seeing your work make a tangible impact on how global commerce moves, this is the place where your skills and judgment truly come to life.

Role Overview: Fulfillment IQ is looking for a dynamic Senior Engineering Manager with 8+ years of software engineering experience, including at least 4 years in engineering leadership, people management, or technical delivery leadership. The Senior Engineering Manager will be responsible for leading high-performing engineering teams in Fulfillment IQ’s AI-assisted, squad-based delivery model. This role combines people leadership, technical execution, customer-facing delivery ownership, architecture contribution, and hands-on engineering across full-stack development, cloud infrastructure, databases, DevOps, and automation-first quality practices. This role is critical to Fulfillment IQ’s next-generation delivery model: builder-led, AI-assisted, architecture-driven, automation-first, and client-outcome focused. The Senior Engineering Manager will lead cross-functional engineering teams across backend, frontend, cloud, DevOps, QA automation, and solution delivery while actively contributing to architecture, design, coding, troubleshooting, customer escalations, and engineering governance. The ideal candidate is not only a people manager, but also a hands-on engineering leader who can operate across C#.NET, Angular, React, Python, SQL Server, PostgreSQL, MongoDB, Azure Infrastructure, Google Cloud Platform, Azure DevOps Pipelines, and modern software delivery practices. Key Responsibilities: Engineering Leadership & People Management: Lead, mentor, and develop engineering teams across backend, frontend, integration, database, cloud, DevOps, and automation domains. Own people management responsibilities, including performance feedback, coaching, career development, capacity planning, and team engagement. Build a high-accountability engineering culture focused on ownership, quality, collaboration, and continuous improvement. Partner with Technical Leads to ensure engineers receive strong technical direction, mentorship, and architectural guidance. Support hiring, onboarding, skill development, and succession planning across engineering roles. Identify skill gaps and build upskilling plans for AI-assisted engineering, cloud, DevOps, automation, and architecture practices. Promote a builder-led culture where engineers are close to customer problems and accountable for solution outcomes.

AI-Assisted Engineering Delivery: Champion AI-assisted engineering practices across software development, testing, documentation, prototyping, debugging, code review, and delivery execution. Establish responsible usage expectations for AI coding assistants and engineering accelerators, ensuring outputs are secure, maintainable, scalable, and aligned with architecture standards. Guide teams in using AI tools to accelerate boilerplate development, unit test creation, documentation, troubleshooting, refactoring, and solution prototyping. Drive practical adoption of AI-assisted engineering tools such as GitHub Copilot, Azure AI, ChatGPT Enterprise, Cursor, or similar platforms. Partner with Technical Leads to define reusable prompts, solution patterns, code templates, engineering playbooks, and accelerators. Measure AI-assisted productivity improvements while protecting quality, reducing rework, and maintaining strong engineering discipline. Ensure AI-generated code is reviewed through appropriate peer review, security review, test coverage, and release validation processes. Build a delivery culture where AI improves engineering velocity without weakening ownership, accountability, or technical judgment.

Delivery Ownership & Execution Governance: Own engineering delivery commitments across assigned projects, clients, delivery squads, or pods. Define technical delivery plans, milestones, estimates, dependencies, risks, and execution timelines. Ensure engineering work aligns with business objectives, product priorities, architecture standards, and client commitments. Drive sprint execution, engineering throughput, delivery predictability, and milestone completion. Partner with Product Owners, Directors of Product, QA, DevOps, Technical Leads, and Project/Delivery teams to ensure backlog readiness and execution clarity. Proactively identify delivery risks, technical blockers, resource constraints, and escalation points. Ensure engineering teams deliver transparency, predictable cadence, and measurable outcomes. Own engineering status reporting, delivery health, technical risk updates, and remediation plans.

Architecture, Design & Technical Governance: Contribute directly to solution architecture, technical design, and implementation planning. Review and validate architecture decisions for scalability, security, maintainability, reliability, and cost efficiency. Partner with Technical Leads to define system design, integration patterns, API standards, cloud design, and deployment architecture. Ensure engineering teams follow…