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Delivery Manager — SaaS Cloud Application (R&D)CGS (Computer Generated Solutions)Canada

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Delivery Manager — SaaS Cloud Application (R&D)

CGS (Computer Generated Solutions)
  • CA
    Canada
  • CA
    Canada

À propos

Overview

Delivery Manager — SaaS Cloud Application (R&D)

Reports to: VP, Research & Development. Type: Full-time.

We’re seeking a hands-on Technical Delivery Manager to drive the end-to-end delivery of a modern SaaS cloud application. You will translate the product roadmap into actionable plans for engineering, run the day-to-day execution (Scrum/Kanban), remove blockers quickly, and ship high-quality releases on schedule. You’re comfortable discussing technologies like Unity3D builds, Heygen, TypeScript/modern web stacks, and AWS architectures—and you champion pragmatic use of AI-assisted development to accelerate delivery while maintaining quality.

Role Summary

Responsibilities
  • Delivery Leadership
  • Own the delivery plan: scope, milestones, dependencies, and critical path across backend, web, and overall delivery.
  • Run daily Scrum, sprint planning, reviews, and retros. Keep teams unblocked and laser-focused on priorities.
  • Maintain a healthy, prioritized backlog; ensure stories have clear acceptance criteria and testability.
  • Track and drive against KPIs (lead time, cycle time, throughput, sprint predictability, escape rate, deployment frequency).
  • Technical Program Execution
  • Collaborate with Tech Leads to break work into epics/stories/tasks aligned to architecture and performance goals.
  • Coordinate build and release schedule and web app deployments (TypeScript/React/Node or similar) across environments.
  • Quality & Release Management
  • Manage external QA resources; define test strategy, coverage goals, and entry/exit criteria per release.
  • Work with contract and/or AI-based quality measures.
  • Orchestrate regression, performance, and security testing; ensure defects are triaged with clear SLAs.
  • Own release notes, change approval, and production readiness checklists.
  • AI-Assisted Development Enablement
  • Promote responsible use of AI coding tools to speed delivery.
  • Track impact on velocity and quality; iterate practices based on evidence.
  • Proactively surface risks, blockers, and decisions; drive mitigations with owners and dates.
  • Liaise with the VP of R&D via daily concise reports and structured weekly updates; escalate early and with options.
  • Align engineering, product, design, and QA around scope, tradeoffs, and timelines.
  • Process Improvement
  • Apply Lean principles to remove waste and reduce WIP; keep teams focused on the smallest shippable value.
  • Evolve team health rituals; ensure clarity of roles, ownership, and working agreements.
Qualifications
  • 5+ years in Technical Project/Program Management delivering SaaS products in production.
  • Working knowledge of modern SaaS pipelines/builds and TypeScript -based modern web development (e.g., React/Next.js, Node).
  • Practical experience with AWS and microservices.
  • Strong Agile execution (Scrum/Kanban), backlog management, story slicing, and acceptance criteria writing.
  • Proven ability to translate roadmaps into epics/stories/tasks and drive cross-functional execution to deadlines.
  • Comfortable reading code, discussing architectures, and facilitating technical trade-offs.
  • Experience coordinating external QA vendors and managing multi-environment release schedules.
  • Demonstrated adoption of AI-assisted development with measurable impact on velocity/quality.
Not Mandatory, But We Would Be Strongly Influenced By…
  • Background in immersive/3D applications or real-time systems.
  • AI assisted-coding success stories that can scale the team.
Tools & Stack (examples) Reporting & Rhythm
  • Daily: Standup + concise written update to VP of R&D (progress, plan, risks, asks).
  • Release Management: Go/No-Go, runbook, rollout plan, incident/rollback procedures.
Success Metrics (first 90–180 days)
  • ≥90% sprint goal attainment with ≤10% scope churn mid-sprint.
  • 20–30% improvement in lead time/cycle time via waste removal and AI enablement.
  • Reduction in escaped defects and MTTR; stable deployment frequency.
  • Predictable release cadence with zero critical-release surprises.

Remote-first with core hours overlapping North America. Occasional travel for planning/on-sites (≤10%). Competitive compensation and benefits commensurate with experience.

#J-18808-Ljbffr
  • Canada

Compétences linguistiques

  • English
Avis aux utilisateurs

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