{
  "schemaVersion": "1.0.0",
  "generatedAt": "2026-06-08T00:00:00.000Z",
  "contentVersion": "git:fd6bd6192f024e161dad661ec60dc207da35b5cf-dirty",
  "roles": [
    {
      "id": "role:applied-ai-engineer",
      "label": "Applied AI Engineer",
      "fit": "strong early-career fit",
      "evidence": [
        "project:datasentinel",
        "project:vault-bridge",
        "project:semantic-video",
        "project:nitro-judge"
      ],
      "strengths": [
        "Public prototypes focus on AI workflow trust, source state, review, audit, and proof boundaries.",
        "Projects show full-stack and system-shaping work rather than only model-output demos.",
        "The site consistently distinguishes what a prototype proves from what it does not prove."
      ],
      "gaps": [
        "production adoption",
        "large-scale reliability data",
        "model-behavior eval depth on real users or operators"
      ],
      "recommendedProofUpgrade": [
        "public eval report",
        "failure taxonomy",
        "operator field note",
        "production-readiness gap memo"
      ],
      "interviewFollowups": [
        "How would you turn lawdit GDPR from a prototype into production-grade privacy workflow software?",
        "Which eval would show that a workflow preserved review state instead of only producing a useful answer?"
      ]
    },
    {
      "id": "role:privacy-trust-engineering",
      "label": "Privacy / Trust Engineering",
      "fit": "strong thematic fit",
      "evidence": [
        "project:datasentinel",
        "project:vault-bridge"
      ],
      "strengths": [
        "lawdit GDPR models personal-data evidence review, redaction, owner routing, and audit.",
        "serverless-vault-bridge separates AI suggestions from durable writes through review and confirmation boundaries.",
        "The public copy names legal, compliance, deletion, security, and production limits explicitly."
      ],
      "gaps": [
        "formal privacy or security review",
        "production tenant integration",
        "enterprise-grade deletion or retention workflow"
      ],
      "recommendedProofUpgrade": [
        "threat model",
        "privacy review checklist",
        "realistic integration architecture",
        "redaction leakage eval"
      ],
      "interviewFollowups": [
        "Where should approval live when an AI system can prepare a sensitive action but should not own the final mutation?",
        "What audit event should be impossible to skip before a sensitive-data workflow earns trust?"
      ]
    },
    {
      "id": "role:agent-workflow-infrastructure",
      "label": "Agent Workflow Infrastructure",
      "fit": "strong thematic fit, not production-scale proven",
      "evidence": [
        "project:vault-bridge",
        "project:datasentinel",
        "project:semantic-video",
        "project:tum-search"
      ],
      "strengths": [
        "The strongest projects preserve boundaries between suggestion, evidence, review, and durable state.",
        "The work treats agent usefulness as a systems problem involving permissions, sources, owners, rollback, and audit.",
        "Public repositories provide inspect paths instead of relying on claims alone."
      ],
      "gaps": [
        "production traffic",
        "long-running observability",
        "multi-tenant permission model",
        "abuse and rate-limit design under real usage"
      ],
      "recommendedProofUpgrade": [
        "read-only API design",
        "MCP threat model",
        "browser-agent interaction test",
        "observable deployment log"
      ],
      "interviewFollowups": [
        "What should happen when a browser or MCP agent misunderstands page content as an instruction?",
        "Which write path would you keep impossible for an agent until a human confirms exact content?"
      ]
    },
    {
      "id": "role:forward-deployed-engineer",
      "label": "Forward Deployed Engineer",
      "fit": "promising but unproven",
      "evidence": [
        "project:datasentinel",
        "project:tum-search",
        "project:aisd-redesign"
      ],
      "strengths": [
        "Projects start from workflow pressure and operator trust rather than abstract technology alone.",
        "The public writing shows concern for handoff, ownership, exceptions, and proof gaps.",
        "The site is explicit about which claims need real field pressure before becoming stronger."
      ],
      "gaps": [
        "real customer rollout",
        "stakeholder management evidence",
        "measurable adoption or workflow impact"
      ],
      "recommendedProofUpgrade": [
        "3-user field test",
        "implementation diary",
        "stakeholder objection log",
        "before-and-after workflow map"
      ],
      "interviewFollowups": [
        "Tell me about a time a working demo failed because the organizational boundary was wrong.",
        "Which public prototype would you deploy first for a real operator, and what would you remove before deployment?"
      ]
    }
  ],
  "doNotInfer": [
    "private-client work",
    "revenue",
    "adoption",
    "production reliability",
    "legal compliance",
    "security posture",
    "procurement fit",
    "senior production ownership"
  ]
}