Implementation Manager

Role Overview

The Implementation Manager will own the end-to-end technical implementation of AI agents built on the platform in client environments. Reporting to the Head of Implementations, this role translates client needs into executable implementation plans and coordinates the systems, people, access, and decisions required to deliver successful deployments.

Key responsibilities

• Own the end-to-end technical implementation of AI agents built on the platform in client environments.
• Define the solution, technical requirements, deliverables, and success criteria, and translate them into a sequenced implementation plan.
• Map the implementation integration surface, including the systems, APIs, and data sources each agent must connect to.
• Manage the collection of required access, credentials, approvals, and technical inputs so delivery remains unblocked.
• Coordinate with engineering on integrations, provisioning, configuration, testing, dependencies, and implementation sequencing.
• Coordinate with AI Operations on context engineering, ensuring each agent has the appropriate knowledge, retrieval mechanisms, and guardrails.
• Act as the client-facing technical owner by leading technical conversations, managing expectations, and controlling scope throughout delivery.
• Build and maintain internal tooling that streamlines the implementation workflow, using AI-driven development where appropriate.
• Maintain a strong working understanding of the platform architecture, including identity, tenancy, module provisioning, the launcher, integrations, and module connectivity.
• Track implementation progress and delivery metrics, surface risks and blockers early, and report status clearly to clients and leadership.
• Maintain accurate implementation documentation, runbooks, and release notes.
• Feed implementation learnings back into the product, identifying recurring integration patterns, gaps, and opportunities to improve the platform.

About You

• Experience in owning technical implementations, SaaS deployments, integrations, or complex client delivery.
• Ability to translate business and client requirements into technical scope, deliverables, success criteria, and implementation plans.
• Working knowledge of APIs, data sources, authentication, provisioning, configuration, and software testing.
• Strong cross-functional coordination skills across clients, engineering, product, and AI or data teams.
• Ability to lead technical client conversations, manage expectations, and protect delivery scope.
• Hands-on comfort with AI-assisted development and internal tooling.
• Excellent documentation, communication, risk management, and organizational skills.