// Variant: Forward Deployed Engineer (FDE) — fde.mathur.dev
// First-draft copy re-angled toward customer-facing build-out and deployment.
// Refine against the FDE-targeted resume PDF when it lands.
(window.RESUME_CONTENT = window.RESUME_CONTENT || {}).fde = {
  meta: {
    role: 'fde',
    docTitle: 'Arpit Dev Mathur — Forward Deployed Engineer',
    resumePdf: 'assets/resume-fde.pdf'
  },

  hero: {
    eyebrow: 'Forward Deployed Engineer · San Francisco',
    tagline: (
      <>
        I build and <em>deploy</em> systems against real customer problems — a
        customer&#8209;service RAG system in production at Asurion, security tooling adopted across
        Windows engineering teams at Microsoft, and an M.S. in Data Science &amp; AI at the
        University of San Francisco.
      </>
    )
  },

  about: {
    lead: "I'm a software engineer who builds and deploys AI systems.",
    paragraphs: [
      <>At Asurion I built a customer&#8209;service RAG system end to end and shipped it against a
        live support workload — the kind of work where the system meets the customer directly.</>,
      <>Before that, six years at Microsoft on Windows core platform: a static analyzer rolled
        out as a triage tool across engineering teams, the WPF port to .NET Core, and a
        rollback framework used during live OS regressions.</>,
      <>I like being where the software meets the problem — building, deploying, and tightening
        the loop with whoever depends on it. 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 system</b> end to end — query paraphrasing, embeddings, re&#8209;ranking, and LLM answer generation — deployed against a live customer&#8209;support workload. (Contract.)</>,
            <><b>Stood up an evaluation harness</b> so embedding, retriever, and re&#8209;ranker choices could be compared on real relevance and answer&#8209;quality metrics — drove the models that went to production.</>,
            <><b>Shipped image understanding</b> into the production chatbot: async LLM extraction pulls context from customer&#8209;sent images straight into the conversation.</>
          ]
        }
      ]
    },
    {
      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 flagged unsafe code patterns across the Windows OS codebase and rolled it out as a triage tool for engineering teams.</>,
            <>Ran it across <b>100s of Windows binaries</b>, surfacing findings in a triage&#8209;friendly SARIF format.</>,
            <>Worked findings to resolution — <b>100+ security issues</b> fixed, 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 unblocking app teams on every Windows upgrade.</>
          ]
        },
        {
          name: 'Known Issue Rollback (KIR)',
          kicker: 'Live mitigation',
          bullets: [
            <>Built a <b>Velocity&#8209;based rollback framework</b> that let Windows revert specific regressions in the field <b>without</b> a full update cycle.</>,
            <>Designed 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.</>
          ]
        }
      ]
    }
  ],

  // FDE: lead with what the customer sees first — ML, then the infra to run it.
  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' }
      ]
    },
    {
      cat: 'Cloud & Infra',
      items: [
        { name: 'Azure', primary: true },
        { name: 'AWS', primary: true },
        { name: 'GCP' },
        { name: 'Docker', primary: true },
        { 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' }
      ]
    }
  ]
};