Kenneth R. Turner

My Experience

I am a Technical Product Manager who delivers enterprise solutions that streamline workflows, reduce operational inefficiencies, and support better decision-making. Over 20 years, I have led application modernization, cloud migration, and portfolio optimization programs at GE Vernova, GE Power, and Alstom Power.

I combine product strategy with technical depth to turn complex systems into scalable solutions that deliver measurable business value. My experience includes working with engineering, data, and architecture teams to define requirements, shape delivery plans, and guide successful implementation.

I use AI prototypes to explore emerging technologies and validate new ideas. These projects highlight my ability to define problem statements, design architectures, evaluate feasibility, and apply AI to real business use cases in a controlled and responsible way.

I am seeking a Technical Product Manager role focused on improving how organizations deliver, scale, and modernize enterprise technology.

AI and Emerging Technology Prototypes

These prototypes demonstrate how I turn enterprise problems into practical MVPs by defining business needs, clarifying technical requirements, and shaping early architecture. Each project explores a different area of AI and data-driven decision support, progressing from structured analysis to semantic search to predictive and generative intelligence.

Across all prototypes, I defined the business problem, data flows, system behavior, user experience, and MVP scope. Generative AI was used to accelerate implementation and code scaffolding, while I focused on product direction, architecture decisions, and validation of technical feasibility.

GenAI App Rationalization Advisor: Designed to streamline application portfolio assessments by reducing manual effort and improving consistency. I defined the workflow and system architecture, while leveraging generative AI to support code generation, data preparation, and automated report creation.

Semantic CMDB Search Tool: Created to improve how teams access configuration data through a natural language interface. I defined search requirements, designed the retrieval and embedding workflow, and outlined the user experience, while AI assisted with prototype logic and UI scaffolding.

AI Benefits Cost and Utilization Analyzer: Planned as a predictive analytics tool for consolidating benefits and claims data into executive-ready insights. I built the Bronze layer of a local Data Lakehouse and defined the future analytics pipeline. Next phases include predictive models, document intelligence, and a conversational interface, all designed to maintain data privacy and security.

GenAI App Rationalization Advisor

• Streamlined application portfolio analysis using an AI-assisted review workflow
• Designed the evaluation framework and outlined planned scoring rules and decision logic for future enhancements
• Leveraged AI to automate recommendations, generate rationalization summaries, and produce PDF/CSV reports
• Developed an interactive local prototype with a Tkinter desktop interface

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Semantic CMDB Search Tool

• Improved CMDB data retrieval by enabling natural-language search across ServiceNow PDI records
• Designed the embedding workflow, retrieval approach, and UI/UX flow
• Used AI to generate portions of the prototype (vector search logic, API scaffolding, and UI components) based on the architecture and requirements I defined
• Implemented using OpenAI embeddings, Chroma DB, FastAPI, and Streamlit

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AI Benefits Cost & Utilization Analyzer

• Provides predictive insights and automated executive summaries for benefits data
• Defined architecture, workflow, and data ingestion strategy
• Built Bronze-layer Data Lakehouse using open datasets (CMS, BLS, Medicare)
• Future phases include predictive modeling, document intelligence, conversational AI, and simulated integration with enterprise HR systems

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