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        "rationale": "Programming languages and domain-specific languages used in Pega development.",
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            "slug": "scala-backend-developer",
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        "skipped_reason": null
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          "source": "db"
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        "role_dimension_saved": true,
        "roles_from_db": [
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            "slug": "full-stack-engineer",
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          {
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            "role_archetype": "Engineering",
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            "source": "db"
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        ],
        "skill_dimension_saved": true,
        "skill_id": 188,
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          "difficulty_hint": "well_known",
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        "roles_from_db": [
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          "source": "db"
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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          "slug": "cloud-security-posture-tools",
          "source": "db"
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        "role_dimension_saved": false,
        "roles_from_db": [
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        "roles_from_db": [
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        "roles_from_db": [
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          "rationale": "Designing request/response shapes and the rules that govern client-server interaction. This cluster is coherent because full stack engineers often own the contract between UI behavior and backend implementation.",
          "slug": "api-design-and-contracts",
          "source": "db"
        },
        "dimension_id": 3,
        "input_skill": "REST",
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
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            "display_name": "Fullstack Developer",
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          "slug": "api-interface-and-contract-design",
          "source": "db"
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        "dimension_id": 289,
        "input_skill": "REST",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
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            "display_name": "Go Backend Developer",
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          "rationale": "Standards and protocols for integrating Pega applications.",
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          "source": "db"
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
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            "display_name": "Pega Developer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "pega-developer",
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          "id": 452,
          "rationale": "Encompasses key web and data standards, protocols, and compliance requirements relevant to Sitecore implementations.",
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          "source": "db"
        },
        "dimension_id": 452,
        "input_skill": "REST",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Sitecore Dev",
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            "rationale": null,
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        "skill_dimension_saved": true,
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          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
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        },
        "dimension_id": 96,
        "input_skill": "LLMs",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1193,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 15,
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          "difficulty_hint": "well_known",
          "display_name": "ML Frameworks and Libraries",
          "id": 40,
          "rationale": "Core libraries used to define models, train them, run inference, and evaluate predictive performance. These frameworks shape how ML engineers express model architectures and training loops.",
          "slug": "ml-frameworks-and-libraries",
          "source": "db"
        },
        "dimension_id": 40,
        "input_skill": "TensorFlow",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
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