Role Overview
The AI Delivery Lead bridges business and technology teams to identify, shape, and deliver AI and automation solutions that create measurable business value. The role combines business engagement, solution design, AI expertise, and delivery coordination, translating business challenges into practical implementation approaches and guiding initiatives from discovery through adoption.
While not a full-time software development role, it requires sufficient technical depth to engage credibly with architects, developers, platform teams, and IT functions; challenge implementation choices; troubleshoot issues; and promote secure, governed, scalable solutions aligned with enterprise architecture and platform standards.
Your Responsibilities
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Assess value, feasibility, risk, implementation effort, and the relative suitability of AI, automation, or combined approaches.
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Guide initiatives across the full lifecycle, from ideation and prototyping through implementation, deployment, and adoption.
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Coordinate business stakeholders, developers, architects, platform teams, and IT functions, maintaining clear ownership and delivery momentum.
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Support troubleshooting, root-cause analysis, and issue resolution, constructively challenging technical approaches where needed.
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Apply modern AI capabilities and design patterns, including Generative AI, agentic AI, Retrieval-Augmented Generation (RAG), orchestration, prompt and harness engineering, and enterprise AI platforms.
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Ensure solutions align with enterprise architecture, security, governance, data, and platform standards.
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Present recommendations, trade-offs, risks, and implementation options clearly to management and technical and non-technical stakeholders.
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Drive adoption, measurable outcomes, continuous improvement, and reuse of successful solution patterns.
Your Profile
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Strong business engagement, stakeholder management, workshop facilitation, and communication skills, with the ability to work credibly with senior business leaders and technical specialists.
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Strong knowledge of Generative AI, agentic AI, RAG, orchestration, prompt and harness engineering, AI solution patterns, and governance considerations.
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Sufficient technical depth to interpret solution designs, engage constructively with technical teams, investigate issues, and challenge implementation approaches.
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Strong analytical, problem-solving, and troubleshooting capabilities, with sound judgement when assessing value, feasibility, risk, and delivery options.
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A collaborative, outcome-oriented mindset and a clear understanding of how AI, automation, data, and technology platforms combine to create business value.
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Understanding of enterprise application architecture, APIs, integrations, cloud platforms, data flows, and modern technology ecosystems.
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Experience with low-code/no-code platforms, workflow orchestration, and process automation, including technologies such as Microsoft Power Automate, Power Platform, or Mendix.