About the Role
AMI Group is expanding its use of artificial intelligence to improve efficiency, automation, and decision-making across non-critical business workflows. To support this effort, we are creating an AI Project Manager role focused on structuring, prioritizing, and delivering AI initiatives across the organization.
This is a business- and project-oriented function, acting as the primary interface between business teams, technical capabilities, and executive decision-making. The AI Project Manager owns the full lifecycle of AI projects, from intake and definition through deployment, adoption, and performance measurement.
Key Responsibilities
Project Intake and Definition
- Serve as the single point of intake for AI project ideas and improvement initiatives submitted by internal teams
- Work directly with stakeholders to clarify business needs and translate them into actionable project definitions, scope, and requirements
- Accompany team members throughout the project discovery phase to ensure alignment between business expectations and proposed solutions
Prioritization & Executive Reporting
- Design and maintain a structured decision pipeline to evaluate, score, and sequence AI initiatives
- Prepare concise project briefs, solution outlines, and prioritized recommendations for executive review and decision-making
- Present the project portfolio to the executive team on a regular cadence, supporting resource allocation and strategic alignment
Project Management & Delivery
- Lead approved AI projects end-to-end, from definition through build, deployment, and adoption
- Directly implement AI solutions, including configuration, integration, and testing, using available AI platforms and tools, taking full technical ownership of each project from prototype to production
- Coordinate with business teams, IT, and external partners to ensure successful and timely implementation
- Track milestones, risks, and deliverables, maintaining clear accountability throughout the project lifecycle
- Ensure AI solutions are deployed into production in alignment with governance, security, cost, and compliance requirements
Performance Measurement & Scalability
- Define, monitor, and report KPIs to measure delivery progress, user adoption, and business impact for each project
- Ensure AI solutions are designed for scalability, reuse, and long-term sustainability within AMI's AI framework
- Contribute to building AMI's AI capability by establishing repeatable processes, templates, and best practices
Technical & Functional Scope
This is not a pure project management role. The AI Project Manager is expected to directly implement AI solutions, from configuration and integration through to deployment. A solid, hands-on understanding of how modern AI systems are built is therefore essential.
AI Platforms & Tools
The AI Project Manager must have working knowledge of commercially available AI platforms and be able to configure and deploy solutions using tools such as Copilot Studio, Azure AI Services, Document Intelligence, AI Foundry, and Claude Code. Platform selection should be grounded in business requirements, taking into account usability, integration complexity, cost, and fit with AMI’s existing infrastructure.
Implementation & Technical Foundations
As the person responsible for building as well as managing AI solutions, the AI Project Manager must understand the core components of modern AI systems. This includes LLMs for reasoning and output generation, APIs for connecting AI solutions to business systems such as ERP platforms, databases, and third-party services, and MCP (Model Context Protocol) for orchestrating agents and tools into scalable, multi-step workflows. More broadly, the role requires a working understanding of Agentic AI, including how autonomous agents can be designed to complete multi-step business tasks, make decisions, and interact with external systems with minimal human intervention.
Feasibility, Risk & Business Alignment
The AI Project Manager must be able to assess what is realistically achievable for a given business problem, weighing technical feasibility against cost, timeline, and operational constraints. This includes understanding risks related to data governance, security, and compliance, and ensuring that solutions are designed for sustainability rather than one-off delivery.
Profile & Requirements
Professional Skills
- Proven ability to structure complex problems, define clear requirements, and manage projects end-to-end
- Strong communication and facilitation skills, equally comfortable working with business stakeholders and executive leadership
- Ability to work autonomously and take full ownership of a project, from initial scoping through to hands-on implementation and delivery
- Analytical mindset with high attention to clarity, structure, and documentation
- Experience preparing and presenting recommendations to senior leadership
Technical Knowledge
- Familiarity with AI platforms and tools (e.g. Copilot Studio, Azure AI services, Claude Code…)
- Understanding of AI workflow automation, data processing concepts, and integration patterns
- Awareness of compliance, risk management, and ethical AI considerations
- Ability to evaluate AI solutions for performance, usability, and alignment with business standards
Mindset & Attributes
- Genuine interest in artificial intelligence, automation, and digital transformation
- Self-starter with the ability to manage multiple initiatives simultaneously
- Comfort operating in ambiguity and translating unclear business needs into structured deliverables
- Collaborative approach with a strong sense of ownership and accountability