Senior Delivery Manager
New
R
Robots & PencilsApplied AI
Canada, Remote FriendlyFull-TimeSenior
Salary160,000 - 200,000 CAD per year
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Job Details
- Experience
- 5+ years of experience in software delivery, technical project management, or engineering leadership
- Required Skills
- SCRUMJiraConfluenceGitHubAzure DevOps
Requirements
- 5+ years of experience in software delivery, technical project management, or engineering leadership.
- Strong understanding of agile delivery practices across complex, multi-team engagements, such as Scrum, SAFe, or Kanban.
- Experience managing distributed teams across onshore and offshore locations.
- Proven ability to deliver complex, multi-platform digital systems in agile environments.
- Strong client-facing communication and relationship management skills.
- Experience with delivery tooling such as Jira, Confluence, GitHub, Azure DevOps, and CI/CD pipelines.
- Familiarity with cloud-native architectures and AI-enabled platforms.
- Demonstrable use of AI tools, such as Claude, for delivery planning, reporting, and documentation.
- Track record leading at least one engagement where AI/ML or agentic capability was core to the solution, including managing model risk, evaluation, and client expectations.
- Experience setting standards for AI-native work, including evaluation criteria, human-in-the-loop checkpoints, and monitoring, and coaching other delivery managers on them.
- Track record leading an agentic development or delivery process, including observability, success metrics, and status visibility.
- PMP, Scrum Master, SAFe, or equivalent certification preferred.
Responsibilities
- Lead end-to-end delivery of complex, multi-phase engagements, aligning scope, budget, timeline, and quality.
- Facilitate sprint planning, backlog refinement, and delivery execution across cross-functional teams.
- Manage phased releases, production readiness, and transitions into operations and maintenance.
- Identify and manage dependencies, risks, scope changes, and escalations.
- Define and report delivery KPIs, using data to guide decisions and delivery tradeoffs.
- Support QA and UAT to validate quality against agreed acceptance criteria.
- Implement AI Development Life Cycle practices and set standards for AI-augmented delivery across engagements.
- Partner with AI/ML engineering leads and product managers on model risk, data readiness, evaluation, observability, and AI-feature definitions of done.
- Serve as the primary delivery contact for clients, leading stakeholder sessions and communicating progress, risks, and tradeoffs.
- Lead and coach distributed delivery teams and junior delivery managers; contribute to delivery practices and staffing decisions.
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