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Description

General Information:

Job Title: Senior Engineering Manager
Location: Toronto, ON (Onsite/Hybrid)
Job Type: Full-Time
Reporting Line: Senior Vice President, Architecture
Hiring Timeline: Immediate
Existing Vacancy: Yes
Application Deadline: Open until Filled
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 coding standards, design principles, secure development practices, and documentation expectations.
• Lead technical design reviews, architecture reviews, code reviews, and production readiness reviews.
• Support modernization efforts involving microservices, cloud-native architecture, APIs, event-driven patterns, and data integration.
• Drive reuse of proven patterns, frameworks, templates, and accelerators across client engagements.

Hands-On Technical Contribution:

• Design, develop, and maintain scalable, secure, and high-performance applications using C#.NET, Angular, React, and Python.
• Provide hands-on troubleshooting across applications, databases, integrations, cloud, and pipeline layers.
• Review and contribute to code where needed, especially for complex modules, escalations, architecture-critical components, and production issues.
• Optimize and manage databases including SQL Server, PostgreSQL, and MongoDB for performance, reliability, and scalability.
• Configure and improve cloud infrastructure including Azure and Google Cloud Platform services.
• Implement and improve CI/CD pipelines using Azure DevOps Pipelines.
• Support engineering teams in resolving complex technical issues, production defects, performance bottlenecks, and deployment failures.
• Maintain enough hands-on depth to earn technical credibility with engineers, clients, and architecture stakeholders.

Cloud, DevOps & Platform Engineering:

• Drive adoption of modern DevOps practices across build, test, deployment, monitoring, rollback, and release management.
• Improve CI/CD automation, deployment frequency, pipeline reliability, and lead time for changes.
• Partner with DevOps Engineers and Technical Leads to standardize pipeline templates, release gates, deployment checks, and environment practices.
• Ensure cloud infrastructure is secure, scalable, observable, and cost-conscious.
• Promote infrastructure-as-code, automated environment provisioning, containerization, and modern deployment models where applicable.
• Strengthen observability using logging, monitoring, alerting, dashboards, and incident response practices.
• Support production readiness, release governance, and operational support models.

Quality Engineering & Automation Partnership:

• Partner with Lead QA, Senior QA Engineers, QA Automation Engineers, and Technical Leads to embed quality earlier in the development lifecycle.
• Ensure engineering teams support test automation, unit testing, integration testing, API testing, and regression readiness.
• Drive reduction in defect leakage, rework, escaped defects, and production incidents.
• Ensure code quality gates are integrated into CI/CD pipelines.
• Support automation-first delivery by encouraging developers to write testable, maintainable, and observable code.
• Participate in root-cause analysis for major defects and ensure corrective actions are implemented.
• Ensure AI-assisted development is balanced by strong test coverage, peer reviews, security reviews, and release validation.

Customer Engagement & Consulting Delivery:

• Act as a customer-facing engineering leader for solution discussions, technical escalations, delivery risks, and production issues.
• Translate client needs into technical execution plans in partnership with Product, Delivery, and Architecture.
• Communicate complex technical topics clearly to client stakeholders, internal leadership, and delivery teams.
• Manage technical escalations with urgency, ownership, and structured remediation.
• Build client confidence through strong technical judgment, delivery transparency, and solution ownership.
• Support pre-sales, discovery, solution estimation, and proposal inputs where required.
• Ensure engineering delivery remains aligned to client outcomes, business value, and Fulfillment IQ standards.

Team Operating Model & Squad Enablement:

• Lead engineering execution within Fulfillment IQ's squad-based delivery model.
• Ensure engineers are aligned to the right squads or pods based on project needs, skills, availability, and delivery priorities.
• Partner with Product, QA, DevOps, WMS/domain SMEs, and Delivery leaders to create cross-functional execution clarity.
• Support Technical Leads as architecture and technical execution anchors within delivery pods.
• Ensure teams understand ownership boundaries, communication cadence, escalation paths, and delivery expectations.
• Promote collaboration across Product, Engineering, QA, Automation, DevOps, and client stakeholders.
• Reduce handoff friction by embedding engineering early in discovery, estimation, solution design, and backlog refinement.

Engineering Metrics, Reporting & Continuous Improvement:

• Track and improve engineering metrics, including velocity, throughput, predictability, defect rate, rework, deployment frequency, and incident resolution time.
• Use data to identify bottlenecks, productivity gaps, quality issues, and process improvement opportunities.
• Establish team-level dashboards for delivery health, quality trends, pipeline performance, and engineering capacity.
• Drive continuous improvement through retrospectives, root-cause analysis, engineering reviews, and process refinement.
• Improve estimation accuracy, sprint completion, backlog flow, and release confidence.
• Report engineering health and risks to SVP Architecture and cross-functional leadership.
  

Required Skills & Experience:

• 8+ years of software engineering experience.
• 4+ years of engineering leadership, people management, or technical delivery leadership experience.
• Strong hands-on proficiency in Python.
• Frontend experience with Angular and React.
• Working knowledge of Python for automation, scripting, data handling, or integration work.
• Strong database experience with SQL Server, PostgreSQL, and MongoDB.
• Proven experience with Azure Infrastructure and/or Google Cloud Platform, including App Services, VMs, Storage, Networking, Identity, Security, and Monitoring.
• Strong experience with Azure DevOps Pipelines, CI/CD automation, branching strategies, build/release workflows, and deployment governance.
• Experience leading cross-functional teams in Agile, Scrum, squad-based, or pod-based delivery models.
• Knowledge of AI-assisted engineering practices and familiarity with tools such as GitHub Copilot, Azure AI, ChatGPT Enterprise, Cursor, or similar platforms.
• Ability to balance strategic leadership with hands-on technical contributions.
• Strong understanding of software architecture, integration patterns, APIs, security, scalability, and production support.
• Experience with code reviews, design reviews, incident management, and engineering quality practices.
• Excellent communication, customer engagement, problem-solving, and stakeholder management skills.

Preferred Qualifications:

• Experience with microservices architecture, distributed systems, and API-first design.
• Strong hands-on proficiency in C#.NET Core and .NET Framework.
• Experience with containerization and orchestration using Docker and Kubernetes.
• Knowledge of cloud security, identity management, secure coding, secrets management, and compliance-aware development.
• Exposure to data analytics, business intelligence, machine learning, or AI-enabled product integrations.
• Experience implementing AI-assisted software engineering practices using tools such as GitHub Copilot, Azure AI, ChatGPT Enterprise, Cursor, or similar platforms.
• Experience building reusable engineerin...