Artificial Intelligence Solutions Lead

Job Title: Artificial Intelligence Solutions Lead
Location/ Work Structure :
Hybrid - Cincinnati, OH

• Lead the evaluation, selection, and implementation of AI platforms, tools, and vendor solutions aligned with companies "buy over build" strategy.
• Design end-to-end AI solution architectures that integrate with existing enterprise systems including Net Suite, Salesforce, Ascend, and other business-critical applications.
• Develop and deploy AI solutions including large language model (LLM) applications, agentic AI workflows, predictive models, and machine learning systems.
• Build proofs-of-concept and minimum viable products (MVPs) for priority AI initiatives.
• Establish AI governance frameworks aligned with responsible AI principles including accountability, fairness, bias detection, security, data privacy, and transparency.
• Partner with business sponsors across Software & Controls, Manufacturing Operations, Sales, Engineering, and Customer Experience to understand requirements and deliver solutions.
• Configure and customize AI platforms through advanced prompt engineering, API integrations, agent development, and low-code/no-code solutions as appropriate.
• Implement data pipelines, model training workflows, and monitoring systems to ensure AI solutions perform reliably in production environments.
• Define key performance indicators (KPIs) and success metrics for each AI initiative and monitor solution performance, accuracy, and business impact.
• Conduct vendor evaluations, manage RFP processes, negotiate contracts, and oversee vendor relationships for AI-related technologies.
• Create and maintain comprehensive technical documentation, implementation guides, coding standards, and AI best practices.
• Provide technical leadership and mentorship to IT team members on AI/ML concepts, tools, and implementation approaches.
• Stay current on emerging AI/ML technologies, industry trends, and best practices, evaluating their applicability to Company use cases.
• Collaborate with the CIO and IT leadership to refine Company's AI strategy based on technical feasibility, resource constraints, and business priorities.
• Lead workshops, demonstrations, and training sessions to drive AI adoption and change management across the organization.
• Prepare executive reports and presentations on AI initiative progress, ROI, and strategic recommendations.

• Deep technical expertise in artificial intelligence and machine learning including large language models (LLMs), generative AI, predictive modeling, and modern AI frameworks.
• Strong hands-on experience with AI platforms and tools such as OpenAI API, Claude API, Lang Chain, Hugging Face, Microsoft Azure AI services, or similar technologies.
• Proficiency in prompt engineering, Retrieval-Augmented Generation (RAG), agentic AI development, and LLM application patterns.
• Advanced programming skills in Python with experience in JavaScript, APIs, and cloud platforms (Azure, AWS, or GCP).
• Proven ability to architect enterprise AI solutions that integrate with ERP, CRM, PLM, and other business systems.
• Strong analytical and problem-solving skills with demonstrated ability to translate complex business requirements into technical solutions.
• Experience with data engineering, ETL processes, data quality management, and working with structured and unstructured data.
• Knowledge of MLOps practices including model deployment, monitoring, versioning, and continuous improvement.
• Excellent communication skills with ability to explain complex technical concepts to non-technical stakeholders at all organizational levels.
• Strong project management capabilities with experience leading AI/ML initiatives from conception through production deployment.
• Ability to work independently, manage multiple priorities, and deliver results in a fast-paced environment with limited resources.
• Strategic thinking with the ability to evaluate technical trade-offs, assess build vs. buy decisions, and provide data-driven recommendations.
• Experience with agile/iterative development methodologies and modern software development practices.
• Understanding of AI ethics, responsible AI principles, and data privacy regulations.