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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Expert Enterprise AI Solutions Architect - **Company:** MatchPoint Solutions - **Location:** Maryland Heights, MO, United States (Remote available) - **Experience:** Expert - **Salary:** $176,800.0 - $187,200.0 - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Information Systems, Information Engineering, Data Governance, Knowledge Management, Machine Learning, Software Deployment, Enterprise Data Management, Information Technology - **Published:** September 27, 2026 - **Apply:** https://www.careerjet.com/jobad/us461794da8ff93b984bc7d9aed77727b3 ## About the Role Bachelor's degree in business, computer science, information systems, product management, data science, or a related discipline is required. A master's degree in a related discipline is preferred. 7 to 10 or more years of experience in product management, digital transformation, or technology strategy, including at least 2 years working on AI, machine learning, or data products. Working understanding of generative and agentic AI, including capabilities, limitations, costs, and risks, sufficient to evaluate feasibility and challenge assumptions. Proven track record of defining success metrics and demonstrating measurable business value from technology initiatives. Strong stakeholder management skills, including the ability to influence senior leaders and cross-functional partners without formal authority. Experience leading discovery, prioritization, product roadmapping, and structured experimentation in an enterprise environment. Excellent written and verbal communication skills, with the ability to communicate effectively with both executive and technical audiences. Preferred Experience with AI, data governance, data products, enterprise knowledge management, semantic technologies, or related initiatives. Familiarity with AI regulation and responsible AI frameworks, such as the NIST AI Risk Management Framework. Experience with change management, organizational adoption, or enterprise transformation programs. Experience in healthcare payer operations, regulated industries, or environments requiring strong privacy, security, auditability, and human oversight. ## Description We are seeking an AI solutions lead to ensure this portfolio remains connected to business strategy and delivers real, measurable value to our stakeholders. This role owns the why and what of enterprise AI solutions: identifying and prioritizing the right use cases, defining success measures, managing stakeholders, and driving adoption. The Enterprise AI Solutions Lead will work closely with product management, application delivery, data engineering, and AI engineering, serving as the bridge between business needs and technical delivery. This is a senior individual contributor role for someone who is equally comfortable working with executives and engineers., Define and maintain the enterprise AI solution roadmap, aligned with business strategy, enterprise architecture, and enterprise data and knowledge roadmaps. Manage an intake process for AI use cases, evaluating opportunities for business value, feasibility, risk, and data readiness. Prioritize use cases that deliver business impact while expanding shared enterprise capabilities such as the enterprise knowledge layer and AI evaluation service into new domains. Own business requirements, success metrics, and acceptance criteria for enterprise AI solutions. Define and track return on investment, adoption, and business outcomes for each solution, and report results to leadership. Run pilots and structured experiments, facilitating clear go, no-go, and scale decisions based on evidence. Serve as the primary point of contact for business stakeholders engaging with the enterprise AI team. Drive change management, user onboarding, and feedback loops so solutions are adopted and deliver sustained value. Partner with AI governance, data governance, legal, cybersecurity, privacy, and compliance teams to ensure AI solutions meet enterprise policy and regulatory requirements. Maintain current documentation for use cases, business requirements, risk assessments, governance decisions, and key product decisions. Tell the story of the enterprise AI program through demonstrations, leadership updates, and success stories that build credibility and demand. Improve AI literacy among business leaders so they can identify strong use cases, understand appropriate decision boundaries, and set realistic expectations. ## Related Videos - [AI PowerPlay: Building High-Impact Teams & Transformative Solutions](https://www.wearedevelopers.com/videos/1005-ai-powerplay-building-high-impact-teams-transformative-solutions) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Microservices? Monoliths? 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