AI Solutions Manager (2026-3273)

Job Summary

The AI Solutions Manager is responsible for defining and executing the organization’s Artificial Intelligence (AI) strategy and roadmap. This role serves as the primary leader for AI initiatives across the enterprise, identifying opportunities to leverage AI technologies to improve operational efficiency, enhance client and talent experiences, drive revenue growth, and create competitive advantages.

They will partner closely with business leaders, technology teams, and external vendors to evaluate, implement, and optimize AI solutions. This individual will be responsible for gathering business requirements, managing vendor relationships, overseeing AI implementations, designing integration strategies, and ensuring AI solutions are successfully embedded within existing business processes and enterprise applications.

The ideal candidate combines strong technical expertise, business analysis skills, solution architecture experience, and vendor management capabilities. They must be comfortable discussing strategic objectives with executives while also working with developers, architects, and vendors on technical implementation details.

Responsibilities

AI Strategy & Roadmap

• Develop and maintain the enterprise AI strategy and multi-year roadmap.
• Identify and prioritize AI opportunities across all departments.
• Evaluate emerging AI technologies, platforms, and industry trends.
• Establish AI governance frameworks, standards, and best practices.
• Support creating business cases and ROI analyses for AI investments.
• Present recommendations and progress updates to leadership.
• Create a framework for prioritizing and measuring AI initiatives.

Business Partnership & Requirements Gathering

• Partner with business leaders to understand operational challenges and strategic objectives.
• Facilitate workshops, discovery sessions, and stakeholder interviews to identify AI opportunities.
• Gather, document, and validate business and technical requirements.
• Translate business needs into solution designs and implementation plans.
• Define success criteria, KPIs, and expected business outcomes.
• Act as a trusted advisor on AI capabilities, limitations, risks, and implementation considerations.

AI Solution Delivery

• Lead end-to-end delivery of AI initiatives from concept through deployment and adoption.
• Manage proof-of-concepts, pilot programs, and enterprise implementations.
• Create implementation roadmaps, project plans, and resource requirements
• Coordinate activities across business stakeholders, developers, vendors, and technology teams.
• Oversee solution testing, validation, deployment, and optimization.
• Measure business outcomes and drive continuous improvement.

Integration & Solution Architecture

• Design and oversee integrations between AI platforms and enterprise applications.
• Define API, middleware, and data architecture requirements for AI-enabled solutions
• Partner with developers and integration teams to build scalable and secure integrations.
• Evaluate integration approaches including APIs, webhooks, event-driven architectures, automation platforms, and middleware solutions.
• Ensure AI solutions can securely access and utilize enterprise data.
• Review vendor technical architectures and integration capabilities during product evaluations.
• Establish standards and best practices for AI solution architecture and integration design.

Vendor Management

• Serve as the primary contact of AI vendor relationships.
• Evaluate AI platforms, products, and service providers.
• Manage vendor performance and implementation deliverables.
• Coordinate technical and business activities with vendor teams.
• Ensure vendor solutions align with security, compliance, and enterprise architecture standards.
• Maintain awareness of vendor roadmaps and emerging capabilities.

Enterprise AI Adoption & Governance

• Develop adoption strategies to maximize business value from AI investments.
• Partner with Change Management and Learning teams to support training and communications.
• Establish AI governance processes and responsible AI guidelines.
• Monitor AI solution usage, adoption, and effectiveness.
• Promote ethical, secure, and compliant use of AI technologies.
• Create documentation, standards, and operating procedures related to AI solutions.

Success Measures

Within the first 12 months, this role will:

• Establish and publish an enterprise AI roadmap.
• Support the IT leadership team in creating an AI governance and vendor evaluation framework.
• Successfully implement multiple AI solutions delivering measurable business value.
• Establish repeatable standards for AI platform integrations.
• Improve operational efficiency through AI-enabled automation and workflow improvements.
• Increase organizational adoption and understanding of AI technologies.
• Develop strong partnerships with business leaders, technology teams, and strategic vendors.
• Deliver measurable ROI from AI investments through productivity gains, cost reduction, revenue growth, or enhanced customer experiences.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Information Systems, Engineering, Business, or related field.
• 5+ years of experience in technology consulting, enterprise applications, solution architecture, product management, business systems, software implementation, or digital transformation roles.
• 3+ years of experience working with AI, Generative AI, machine learning, intelligent automation, or advanced analytics solutions.
• Experience gathering business requirements and translating them into technical solutions.
• Experience managing third-party vendors and technology partners.
• Strong understanding of enterprise application ecosystems and system integration principles.
• Excellent communication, facilitation, presentation, and stakeholder management skills.

Technical Requirements

• Experience designing, implementing, or supporting enterprise integrations.
• Strong understanding of REST APIs, web services, authentication methods, and integration patterns.
• Experience working with APIs, JSON, XML, webhooks, and data transformation concepts.
• Understanding of cloud-based SaaS architectures and integration methodologies.
• Ability to review technical documentation and collaborate effectively with developers and architects.
• Knowledge of enterprise security principles, data governance, and compliance considerations.

Preferred Qualifications

• Experience implementing AI platforms such as OpenAI, Azure AI, Microsoft Copilot, Anthropic, Google Gemini, AWS AI Services, or similar technologies.
• Experience with Microsoft Dynamics, Workday, Power Platform, Databricks, or other enterprise business applications.
• Experience with integration technologies such as Azure Integration Services or similar platform
• Experience with AI agents, workflow automation, conversational AI, and intelligent process automation.

Preferences

Candidates with additional and relevant experience, education, licensing, or certification beyond the role’s requirements and/or specific to the nature of Prolink’s business will be given additional consideration in the candidate selection process. If all minimum requirements are met, candidates with unique and/or diverse qualifications will also be given additional consideration.