Senior Delivery Manager, Enterprise AI

Lazer

Location: Canada Workplace: RemoteFull-TimeSenior

Salary not disclosed

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Job Details

Experience: 7+ years
Required Skills: Problem SolvingDocumentationClient relationship managementStakeholder managementProcess improvement

Requirements

7+ years at a top-tier consulting firm (McKinsey, BCG, Accenture, Deloitte, or equivalent) or an enterprise technology services environment; you have a proven track record delivering complex software initiatives end-to-end — owning scoping, execution, and launch.
Strong commercial instinct; you've managed enterprise client relationships worth $1M+ and know how to turn strong delivery into expanded engagements.
Deep experience working directly with enterprise clients in a B2B or services environment; you manage relationships across C-suite, product, and engineering simultaneously, navigate ambiguity, and maintain trust in high-pressure, multi-stakeholder environments.
Strong operator with an unblocking mentality; you surface risks early, introduce structure where there is none, improve how teams work, and take ownership of getting work across the finish line.
Comfortable operating on-site with clients; periodic embedded engagement is an expectation of this role.
AI-forward in how you work; you use AI tools daily to automate your own workflows — status updates, reporting, communications — so your time stays focused on the relationships and decisions that only you can handle.
Technically fluent; you can work closely with engineers, understand system constraints, and translate clearly between technical execution and business outcomes.

Responsibilities

Own delivery end-to-end; scope projects with clients and engineering teams, define clear roadmaps, break work into phases, identify dependencies, and maintain momentum across large-scale, multi-workstream engagements through shifting priorities.
Be the structure your client cannot build themselves; define workstreams, establish operating cadence, and bring clarity to complex, ambiguous environments — and own the narrative of every engagement so every deliverable is paired with a clear story of its impact, tradeoffs, and next steps.
Navigate and actively manage multiple stakeholders; maintain a clear view of decision-makers, influencers, and blockers, and ensure alignment across product, engineering, and leadership.
Act as a forward deployed operator; embed with client teams on-site on a periodic basis, understand internal dynamics, and drive outcomes from within the client's environment.
Communicate status before anyone has to ask; provide consistent, structured updates that clearly outline progress, risks, and upcoming decisions.
Unblock teams and drive execution; surface obstacles early, facilitate planning, own the scope boundary, manage change requests, and ensure every meeting delivers actionable outcomes.
Translate between technical and business contexts; communicate engineering constraints clearly to clients and ensure engineers understand business priorities and tradeoffs.
Coach engineers to operate as independent consultants, not ticket-takers; reinforce proactive communication, client ownership, and the ability to navigate enterprise environments confidently.
Improve how teams operate; assess existing processes, identify inefficiencies, and introduce better structure to increase delivery velocity and quality.
Drive AI adoption within engagements; identify opportunities to improve team productivity and client outcomes through AI-enabled workflows, and set the standard for how the team uses AI in their day-to-day.
Identify and drive expansion opportunities; turn delivery success into additional scope, teams, or long-term engagements through strong client trust and strategic insight.
Leave the client stronger than you found them; ensure knowledge transfer, documentation, and process improvements that enable the client to operate more effectively long-term.

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