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jkelleman/README.md

Hi there

I'm Jen, and I design intuitive data experiences.

I'm a Staff Product Designer and Systems Thinker who specializes in building AI-powered UX for data platforms. I love working at the intersection of AI, data systems, and great product design. Most of my time is spent thinking about how to make complex technical systems more accessible and intuitive to use.

What I do

My work spans across:

AI & Machine Learning - I design and build AI agent frameworks, work with LLMs, and create tools that help teams deploy machine learning systems in production. I'm particularly interested in making AI more reliable and easier to integrate into real-world applications.

Data Integration - I've spent years building data pipelines and integration systems. Whether it's streaming data, ETL workflows, or connecting disparate systems, I focus on making data flow smoothly and reliably.

Product Design - I believe great developer tools should be both powerful and delightful to use. I spend a lot of time thinking about API design, documentation, and developer experience.

Software Development - I write code in Python, TypeScript, and other languages. I've built everything from backend services to full-stack applications, always with an eye toward clean architecture and maintainability.

Get in touch

I'm based in Boston, Massachusetts. You can find me on:

Always happy to chat about AI systems, data design, or interesting technical challenges. Feel free to reach out.

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    MCP agent for semantic metrics governance with built-in trust scoring, lineage visualization, and conversational metric definition. Designed for data teams working with dbt, LookML, and modern sema…

    Python 3

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    A Claude Code workspace that transforms ideas into multi-format content: research → long-form articles → platform-specific versions (LinkedIn, newsletter, social media, podcast Q&A)

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    MCP agent translating natural language questions into explainable, reproducible data insights with built-in quality checks and semantic layer integration.

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    Forked from BruceTraining/MCP-Oreilly-1

    Production-ready Model Context Protocol (MCP) agents for content design, meeting organization, and documentation management.

    Python 1

  6. wedding-planning-agent wedding-planning-agent Public

    Treating wedding planning as a data platform problem. Portfolio piece showcasing systems design, semantic modeling & coherent workflows.

    Python 1