Senior Delivery Manager, Enterprise AI
Employees worldwideFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 7+ years
- Required Skills
- CI/CDClient relationship managementRisk ManagementStakeholder managementProcess improvement
Requirements
- 7+ years at a top-tier consulting firm (McKinsey, BCG, Accenture, Deloitte, or equivalent) or an enterprise technology services environment
- Proven track record delivering complex software initiatives end-to-end — owning scoping, execution, and launch.
- Managed enterprise client relationships worth $1M+
- Deep experience working directly with enterprise clients in a B2B or services environment
- 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
- Comfortable operating on-site with clients; periodic embedded engagement is an expectation.
- AI-forward in how you work; use AI tools daily to automate workflows
- Technically fluent; can work closely with engineers, understand system constraints, and translate between technical execution and business outcomes.
- Experience working on AI-driven products or internal tooling (Nice-to-Have)
- Strong understanding of modern development workflows, including AI-assisted coding, CI/CD, and scalable engineering practices (Nice-to-Have)
- Experience operating in forward deployed engineering (FDE) or embedded delivery models (Nice-to-Have)
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.
- 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 visibility and accountability; ensure all progress, decisions, and deliverables are consistently documented and accessible across stakeholders.
- Drive AI adoption within engagements; identify opportunities to improve team productivity and client outcomes through AI-enabled workflows.
- 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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