// Variant: AI Engineer / AI Developer — ai.mathur.dev (also the apex default).
// Shared shell lives in app.jsx; only role-specific copy lives here.
(window.RESUME_CONTENT = window.RESUME_CONTENT || {}).ai = {
  meta: {
    role: 'ai',
    docTitle: 'Arpit Dev Mathur — Software & AI Engineer',
    resumePdf: 'assets/resume-ai.pdf'
  },

  hero: {
    eyebrow: 'Software & AI Engineer · San Francisco',
    tagline: (
      <>
        I build systems that help machines <em>understand</em> — currently working on
        retrieval and evaluation for 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 now building AI systems.",
    paragraphs: [
      <>I spent six years at Microsoft on Windows core platform problems (static analysis,
        cross&#8209;platform .NET, and a rollback framework used during live OS regressions), then
        went back to school to go deeper on ML.</>,
      <>These days I'm most interested in the seam between classical software engineering and
        modern ML: evaluation harnesses, retrieval pipelines, and the operational glue that
        makes LLM&#8209;based products reliable enough to ship.</>,
      <>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>Designed and built a RAG system</b> for customer&#8209;service queries — query paraphrasing, embeddings, re&#8209;ranking, and LLM&#8209;based answer generation. (Contract.)</>,
            <><b>Built an evaluation harness</b> for data&#8209;driven comparison of embeddings, retrievers, and re&#8209;rankers using relevance and answer&#8209;quality metrics — drove model selection for production.</>,
            <><b>Shipped an image&#8209;processing tool</b> for the production chatbot: LLM calls extract context from images and inject it into the conversation flow asynchronously.</>
          ]
        }
      ]
    },
    {
      when: { start: 'Aug 2016', end: 'Dec 2022' },
      title: 'Software Engineer',
      company: 'Microsoft',
      loc: 'Redmond, WA',
      projects: [
        {
          name: 'Retrodict',
          kicker: 'Static analysis',
          bullets: [
            <>Developed a <b>static code analyzer</b> identifying unsafe code patterns across the Windows OS codebase.</>,
            <>Analyzed <b>100s of Windows binaries</b>, surfacing findings in a triage&#8209;friendly SARIF format.</>,
            <>Resolved <b>100+ security issues</b>, saving an estimated <b>$1M+</b> in bounty payouts and remediation cost.</>
          ]
        },
        {
          name: 'Windows Presentation Foundation',
          kicker: '.NET Core port',
          bullets: [
            <>Migrated WPF to <b>.NET Core</b>, porting <b>over a million lines of code</b> and making WPF apps OS&#8209;agnostic — saving app developers time on every Windows upgrade.</>
          ]
        },
        {
          name: 'Known Issue Rollback (KIR)',
          kicker: 'Live mitigation',
          bullets: [
            <>Built a <b>Velocity&#8209;based rollback framework</b> enabling selective Windows rollbacks <b>without</b> a full update cycle when regressions appeared.</>,
            <>Designed the <b>Azure backend</b> for remote group&#8209;policy modification — reducing customer impact 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.</>
          ]
        }
      ]
    }
  ],

  // Group order is the role-tuning lever — recruiters scan the first group hardest.
  skills: [
    {
      cat: 'AI / ML',
      items: [
        { name: 'LLMs', primary: true },
        { name: 'RAG', primary: true },
        { name: 'Embeddings', primary: true },
        { name: 'Re-Ranking' },
        { name: 'Evaluation Pipelines', primary: true },
        { name: 'Vector Databases' },
        { name: 'PyTorch' },
        { name: 'NumPy' },
        { name: 'Pandas' },
        { name: 'Scikit-Learn' },
        { name: 'Deep Learning' },
        { name: 'Regression' },
        { name: 'Classification' },
        { name: 'Unsupervised Learning' }
      ]
    },
    {
      cat: 'Languages',
      items: [
        { name: 'Python', primary: true },
        { name: 'SQL', primary: true },
        { name: 'C#' },
        { name: 'C++' }
      ]
    },
    {
      cat: 'Cloud & Infra',
      items: [
        { name: 'Azure', primary: true },
        { name: 'AWS' },
        { name: 'GCP' },
        { name: 'Docker' },
        { name: 'Flask' }
      ]
    },
    {
      cat: 'Data',
      items: [
        { name: 'PySpark' },
        { name: 'Spark' },
        { name: 'ETL' },
        { name: 'MongoDB' }
      ]
    }
  ]
};