Vice President, AI Solutions & Delivery

About the Role The Vice President, AI Solutions & Delivery will lead solution strategy, architecture, and delivery quality across MGT’s AI initiatives, with a primary focus on client-facing AI revenue and delivery. This is a builder-leader role that requires engaging executives, shaping opportunities, architecting practical AI solutions, guiding technical teams, and ensuring delivery quality from discovery through implementation. What You'll Do

• Lead AI solutioning for external client opportunities, including discovery, technical scoping, architecture, and delivery planning.
• Translate complex business problems into practical AI solutions that can be built, implemented, and supported.
• Partner with consultants, subject matter experts, and client stakeholders to shape high-value AI use cases.
• Support proposals, pursuits, demonstrations, and executive-level client conversations.
• Set architecture standards for AI solutions across client-facing and internal work.
• Guide solution design across LLM applications, RAG pipelines, agentic workflows, data pipelines, integrations, analytics, and model/tool selection.
• Establish reusable design patterns, components, templates, and accelerators.
• Ensure solutions are scalable, secure, maintainable, and aligned with client needs.
• Own quality standards for AI delivery across client engagements and internal builds.
• Review technical designs, delivery plans, implementation risks, and production-readiness considerations.
• Help teams move from prototype to production-ready AI solutions.
• Partner with internal operations and governance leaders to ensure delivery aligns with policies, data handling requirements, and stakeholder expectations.
• Mentor AI Solutions Architects, Data Engineers, Data Scientists, and other technical builders.
• Help define the AI builder talent model, including role expectations, growth paths, and delivery standards.
• Provide technical coaching to teams working across internal MGT priorities and external client projects.
• Build a culture of practical shipping, strong documentation, reusable delivery patterns, and delivery accountability.
• Support internal AI product development where architecture, data, or delivery expertise is needed.
• Contribute to MGT’s AI tool suite, accelerators, methods, and implementation playbooks.
• Identify repeatable solutions that can be packaged across clients or internal use cases.
• Partner with the VP, AI Strategy & Operations on portfolio visibility, resourcing, and delivery readiness. What We're Looking For
• Strong technical fluency across modern AI solution patterns, including LLM applications, RAG, agentic workflows, prompt engineering, vector databases, data pipelines, and integrations.
• Experience designing practical AI, data, analytics, or software solutions that solve real business problems.
• Demonstrated ability to lead technical teams that ship production-quality work.
• Ability to translate business needs into technical architectures, delivery plans, and implementation roadmaps.
• Strong understanding of production delivery considerations, including scalability, maintainability, security, governance, and user adoption.
• Executive presence with the ability to communicate effectively with clients, consultants, engineers, and senior leadership.
• Ability to support business development, proposal strategy, client demonstrations, and pursuit conversations.
• Strong architecture review skills, with the ability to identify design gaps, delivery risks, and practical remediation paths.
• Builder mentality with strong delivery instincts and a bias toward practical implementation.
• Ability to mentor technical talent and create delivery standards, documentation norms, and reusable solution patterns.
• Comfort operating in a fast-moving environment where solutions, teams, and delivery models are still being built.
• Education: Bachelor’s degree in Computer Science, Information Technology, Data Science, Engineering, or Business. Education and Experience
• Bachelor’s degree in Computer Science, Information Technology, Data Science, Engineering, Business, or related field. (Note: the source text indicates typical requirements for this role.)