// Variant: AI Product Manager (AIPM) — aipm.mathur.dev
// First-draft copy re-angled toward cross-functional shipping and product judgment.
// Refine against the AIPM-targeted resume PDF when it lands.
(window.RESUME_CONTENT = window.RESUME_CONTENT || {}).aipm = {
  meta: {
    role: 'aipm',
    docTitle: 'Arpit Dev Mathur — AI Product Manager',
    resumePdf: 'assets/resume-aipm.pdf'
  },

  hero: {
    eyebrow: 'AI Product Manager · San Francisco',
    tagline: (
      <>
        I help AI products actually <em>ship</em> — six years shipping Windows platform
        features at Microsoft, now building and evaluating production LLM systems at Asurion,
        and finishing an M.S. in Data Science &amp; AI at the University of San Francisco.
      </>
    )
  },

  about: {
    lead: "I'm a software engineer who builds AI products.",
    paragraphs: [
      <>I spent six years at Microsoft shipping Windows core platform work — static analysis,
        the WPF port to .NET Core, and Known Issue Rollback, a framework used during live OS
        regressions — then went back to school to go deeper on ML.</>,
      <>What I care about is the seam between engineering and product: deciding what to build,
        what makes an LLM&#8209;based product reliable enough to ship, and turning model choices
        into data&#8209;driven decisions instead of guesses.</>,
      <>Off&#8209;screen: hikes, weightlifting, growing plants.</>
    ]
  },

  roles: [
    {
      when: { start: 'Oct 2025', end: 'Present', now: true },
      title: 'AI Engineer',
      company: 'Asurion',
      loc: 'San Francisco, CA',
      projects: [
        {
          bullets: [
            <><b>Built a customer&#8209;service RAG product</b> end to end — paraphrasing, retrieval, re&#8209;ranking, and LLM answers — aimed at faster, more accurate support responses. (Contract.)</>,
            <><b>Created an evaluation harness</b> that made model choice a data&#8209;driven decision — comparing embeddings, retrievers, and re&#8209;rankers on relevance and answer quality to pick what shipped.</>,
            <><b>Shipped image understanding</b> for the production chatbot — async LLM extraction lets customers troubleshoot with photos instead of describing the problem.</>
          ]
        }
      ]
    },
    {
      when: { start: 'Aug 2016', end: 'Dec 2022' },
      title: 'Software Engineer',
      company: 'Microsoft',
      loc: 'Redmond, WA',
      projects: [
        {
          name: 'Retrodict',
          kicker: 'Static analysis',
          bullets: [
            <>Built a <b>static code analyzer</b> that surfaced unsafe code patterns across the Windows OS codebase.</>,
            <>Triaged findings across <b>100s of Windows binaries</b> using a SARIF&#8209;based workflow.</>,
            <>Closed <b>100+ security issues</b> — an estimated <b>$1M+</b> in bounty and remediation cost avoided.</>
          ]
        },
        {
          name: 'Windows Presentation Foundation',
          kicker: '.NET Core port',
          bullets: [
            <>Ported WPF to <b>.NET Core</b> — <b>over a million lines of code</b> — making WPF apps OS&#8209;agnostic and saving app teams time on every Windows upgrade.</>
          ]
        },
        {
          name: 'Known Issue Rollback (KIR)',
          kicker: 'Live mitigation',
          bullets: [
            <>Built and shipped <b>Known Issue Rollback</b> — a framework to revert specific Windows regressions <b>without</b> a full update cycle.</>,
            <>Defined the <b>Azure backend</b> for remote group&#8209;policy changes, cutting the customer&#8209;impact window during critical regressions by over a month.</>
          ]
        }
      ]
    },
    {
      when: { start: 'May 2015', end: 'Aug 2015' },
      title: 'Software Engineer Intern',
      company: 'Microsoft',
      loc: 'Redmond, WA',
      projects: [
        {
          name: 'Cortana — voice mail',
          kicker: 'Intern project',
          bullets: [
            <>Prototyped and shipped <b>voice&#8209;activated email</b> in Cortana — end&#8209;to&#8209;end hands&#8209;free dictation and send.</>,
            <>Added proactive launch: Cortana would read incoming mail from a chosen sender list and offer to reply or mark unread.</>
          ]
        }
      ]
    }
  ],

  // AIPM: lead with the product surface — ML, then the platform it runs on.
  skills: [
    {
      cat: 'AI / ML',
      items: [
        { name: 'LLMs', primary: true },
        { name: 'RAG', primary: true },
        { name: 'Embeddings', primary: true },
        { name: 'Evaluation Pipelines', primary: true },
        { name: 'Re-Ranking' },
        { name: 'Vector Databases' },
        { name: 'PyTorch' },
        { name: 'Pandas' },
        { name: 'Scikit-Learn' }
      ]
    },
    {
      cat: 'Cloud & Infra',
      items: [
        { name: 'Azure', primary: true },
        { name: 'AWS' },
        { name: 'GCP' },
        { name: 'Docker' },
        { name: 'Flask' }
      ]
    },
    {
      cat: 'Languages',
      items: [
        { name: 'Python', primary: true },
        { name: 'SQL', primary: true },
        { name: 'C#' },
        { name: 'C++' }
      ]
    },
    {
      cat: 'Data',
      items: [
        { name: 'PySpark' },
        { name: 'Spark' },
        { name: 'ETL' },
        { name: 'MongoDB' }
      ]
    }
  ]
};