Remote job
AI Delivery Lead, Enterprise
Job details
About this role
Role overview
Lead the end-to-end delivery of an enterprise AI platform and its agents, from initial kickoff through production launch and early customer success. This role combines program ownership, AI solution quality, enterprise relationship management, and cross-functional leadership to ensure deployments work reliably in real operating environments and deliver measurable customer value.
Responsibilities
- Own deployment plans, milestones, dependencies, risks, and accountability across internal and customer teams. - Design and run user acceptance testing around real workflows, identifying edge cases, hallucinations, integration gaps, and other quality issues before launch. - Ensure solutions remain robust when data is incomplete, systems vary, and requirements evolve. - Serve as the primary customer contact during implementation and early production, leading onboarding, documentation, training, and enablement. - Track adoption and performance after launch, create value dashboards, and resolve barriers to achieving early value milestones. - Coordinate engineering, product, sales, and forward-deployed engineering resources; turn customer feedback into product improvements and hand stabilized accounts to Customer Success.
Requirements
- Strong working fluency with AI systems and the ability to assess how they behave in production environments. - Experience leading complex deployments or programs with multiple technical and customer-facing stakeholders. - Excellent written, verbal, and executive communication skills, including confidence presenting to C-level audiences. - Ability to investigate ambiguous problems, develop practical solutions without established playbooks, and maintain delivery focus. - Customer-oriented judgment, with the ownership mindset to manage both relationship quality and technical outcomes. - Capability to lead and prioritize the work of a team of forward-deployed engineers.
Benefits and work setup
- A central role connecting AI engineering work with measurable enterprise outcomes. - Direct involvement in deploying AI systems at enterprise scale, beyond demonstrations or theoretical use cases.