Senior Technical Project Manager (AI-Forward)

Stacktics Inc.•Toronto, ON

13h•Remote

About The Position

Stacktics delivers Digital Ecosystem Transformation at enterprise scale, working across Cloud Computing, Data Analytics, and Digital Marketing. We're deepening our strategic partnership with Google Cloud, and our Project Delivery function is building out what we call Stacktics 2.0. This is our AI-first evolution of how we plan, deliver, and govern projects, aligned with the industry's shift toward the AI-Driven Development Lifecycle (AIDLC), where AI acts as a genuine collaborator across the project lifecycle rather than a tool applied to individual tasks. The Senior Technical Project Manager (Sr TPM) leads delivery on our most strategic engagements, spanning Google Cloud AI implementations, Data Modernization, and Cloud Infrastructure. This is an individual contributor role reporting to the Head of Project Operations. You'll apply the Stacktics Delivery Methodology day to day and help establish what AI-forward delivery looks like in practice as this function grows.

Requirements

5–7 years of progressive IT Project or Program Management experience in Consulting, Professional Services, or an Agency setting, including enterprise-scale Cloud, Data, or AI initiatives.
Experience managing cross-functional teams and external client stakeholders, including C-level, in a fast-paced environment.
Strong hands-on experience with Jira and Tempo, plus working knowledge of Confluence.
Comfortable with cloud ecosystems. Google Cloud Platform experience preferred.
Experience using Gemini and other AI assistants such as Claude for project work, with a practical sense of where automation genuinely helps.
Working knowledge of prompt engineering concepts, and able to speak plainly about AI's limitations, such as hallucinations and data quality issues.

Nice To Haves

PMP or equivalent formal project management training preferred. CSM or PMI-ACP is a plus.
Familiarity with the Google ecosystem and digital marketing tools is a plus.

Responsibilities

Lead planning, execution, and delivery of technical programs spanning Google Cloud migrations, MLOps, and data engineering pipelines, coordinating Cloud Architects, Data Engineers, and AI Specialists across distributed teams and external partners.
Run a hybrid delivery framework that blends PMI discipline with Agile/Scrum practice, including backlog refinement, sprint planning, and daily stand-ups.
Take projects from milestones and a detailed WBS through Jira setup, backlog grooming, and sprint-ready work. Keep clients informed through recurring touchpoints, and track budget against actuals, reporting variances along with recommendations. Jira and Tempo are central to how we track both delivery and financials.
Spot delivery risks early, whether technical, resourcing, or schedule-related, and manage them through to resolution. Escalate where needed before they become client-facing issues.
Own the financial health of assigned projects, including budget, forecasting, and margin, and enforce change control on scope and fixed-fee engagements.
Give the Head of Project Operations proactive resourcing signals to support hiring decisions and keep workloads sustainable.
Act as the main client-facing point of contact, adjusting status reports, dashboards, and presentations for audiences ranging from technical leads to C-level executives.
Work with sales and pre-sales on land-and-expand opportunities and on Change Orders and SOWs. Contribute to our delivery playbook: lessons learned, estimation templates, and best practices.
Use AI and automation where it actually saves time, such as drafting WBSs and executive reports, or turning meeting notes into action items. Gemini and other assistants like Claude are the main tools for this.
Work within an AI-integrated Agile process, where AI-assisted backlog refinement, sprint planning, and retrospectives are the norm, so more time goes into judgment calls and stakeholder conversations than manual documentation.
Use human-in-the-loop automation to streamline recurring approvals and change-control steps, while keeping people accountable for the decisions that matter.
Pilot and evaluate new AI tools for Project Delivery, and check AI-generated output for accuracy before it's used.