feat(interview): 직군 다중 선택 지원

한 면접 세션에서 여러 직군 질문을 함께 출제할 수 있게 한다. 모드는
단일 유지. 기존 interview_sessions.job_category 는 대표 직군(첫 선택)으로
유지해 하위호환, 전체 직군은 session_job_categories(V14)에 저장.

- DB: session_job_categories 테이블 + 기존 행 백필.
- Core: InterviewSession.jobCategories(@ElementCollection), 요청/커맨드/이벤트/
  payload/응답을 직군 리스트로 확장(대표 직군 병행 노출). 규칙 제목도
  다중 직군("프론트엔드·백엔드 기술 면접")으로.
- AI: generate.questions job_categories 리스트 + 프롬프트 균형 분배 지시.
- FE: CheckboxCardGroup 신규, JobCategorySelector 다중화, 셋업 폼/히스토리
  카드 반영, OpenAPI 타입 재생성.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

Author: i3months

ai/src/ai_server/chain/prompts/question_generation.py

@@ -14,7 +14,7 @@
 )
 
 HUMAN_PROMPT = (
-    "직군: {job_category}\n"
+    "직군(복수 가능): {job_categories}\n"
     "면접 모드: {mode}\n"
     "최대 질문 수: {max_questions}\n\n"
     "지원자 컨텍스트 (이력서/레포 분석):\n"
@@ -25,10 +25,11 @@
     "1. 정확히 {max_questions}개의 질문을 생성하되, **서로 다른 주제/영역**을 다룹니다 "
     "(각 질문이 일반질문 1개의 씨앗이 되고 뒤에 꼬리질문이 붙으므로 같은 주제 반복 금지).\n"
     "2. 각 질문에 적절한 category 를 부여합니다.\n"
-    "3. 직군({job_category})·면접 모드({mode}) 에 맞는 비중으로 카테고리 분배:\n"
+    "3. 직군({job_categories})·면접 모드({mode}) 에 맞는 비중으로 카테고리 분배:\n"
     "   - TECHNICAL: CS_FUNDAMENTAL + TECH_CHOICE + PROJECT_DEEP_DIVE 중심.\n"
     "   - PERSONALITY: BEHAVIORAL 중심.\n"
     "   - INTEGRATED: 모두 균형.\n"
+    "   직군이 여러 개면 각 직군에 질문이 고르게 분배되도록 합니다.\n"
     "   자료가 받쳐주는 만큼만 분배하고, 근거 없는 카테고리를 억지로 채우지 마세요.\n"
     "4. 각 질문에 target_evidence 와 expected_signal 을 채웁니다:\n"
     "   - target_evidence: 질문의 근거가 된 컨텍스트 원문을 짧게 인용. "

ai/src/ai_server/chain/question_generation_chain.py

@@ -28,7 +28,7 @@ class QuestionGenerator(Protocol):
     async def generate(
         self,
         *,
-        job_category: str,
+        job_categories: list[str],
         mode: str,
         max_questions: int,
         context: str,
@@ -43,15 +43,15 @@ def __init__(self, chain: Runnable) -> None:
     async def generate(
         self,
         *,
-        job_category: str,
+        job_categories: list[str],
         mode: str,
         max_questions: int,
         context: str,
         recent_questions: list[str] | None = None,
     ) -> GeneratedQuestionPool:
         result = await self._chain.ainvoke(
             {
-                "job_category": job_category,
+                "job_categories": ", ".join(job_categories),
                 "mode": mode,
                 "max_questions": max_questions,
                 "context": context,

ai/src/ai_server/messaging/consumers/questions_consumer.py

@@ -86,7 +86,7 @@ async def handle(self, message: AbstractIncomingMessage) -> None:
 
             context_text = await self._build_context(req)
             pool = await self._generator.generate(
-                job_category=req.job_category,
+                job_categories=req.job_categories,
                 mode=req.mode,
                 max_questions=effective_pool_size,
                 context=context_text,
@@ -173,7 +173,7 @@ def _build_context(documents: list[DocumentContext]) -> str:
 def _build_initial_rag_query(req: GenerateQuestionsRequest) -> str:
     parts = [
         f"mode: {req.mode}",
-        f"job category: {req.job_category}",
+        f"job categories: {', '.join(req.job_categories)}",
     ]
     for d in req.documents:
         doc_parts = [f"document #{d.document_id} {d.source_type}"]

ai/src/ai_server/model/messages/questions.py

@@ -32,7 +32,8 @@ class GenerateQuestionsRequest(BaseModel):
 
     session_id: int
     mode: InterviewMode
-    job_category: JobCategory
+    # 직군 다중 선택. 첫 항목이 대표 직군.
+    job_categories: list[JobCategory] = []
     documents: list[DocumentContext] = []
     initial_question_count: int = 1
     max_questions: int = 10

ai/tests/test_question_generation_chain.py

@@ -27,7 +27,7 @@ async def test_generate_forwards_formatted_recent_questions_to_chain():
     generator = LlmQuestionGenerator(chain)
 
     await generator.generate(
-        job_category="BACKEND",
+        job_categories=["BACKEND", "FRONTEND"],
         mode="TECHNICAL",
         max_questions=3,
         context="ctx",
@@ -36,3 +36,4 @@ async def test_generate_forwards_formatted_recent_questions_to_chain():
 
     chain_input = chain.ainvoke.call_args.args[0]
     assert chain_input["recent_questions"] == "- 이전 질문"
+    assert chain_input["job_categories"] == "BACKEND, FRONTEND"

ai/tests/test_questions_consumer.py

@@ -79,7 +79,7 @@ async def test_consumer_generates_questions_and_publishes_callback():
         {
             "sessionId": 99,
             "mode": "TECHNICAL",
-            "jobCategory": "BACKEND",
+            "jobCategories": ["BACKEND"],
             "documents": [
                 {
                     "documentId": 1,
@@ -97,7 +97,7 @@ async def test_consumer_generates_questions_and_publishes_callback():
 
     generator.generate.assert_awaited_once()
     call = generator.generate.await_args
-    assert call.kwargs["job_category"] == "BACKEND"
+    assert call.kwargs["job_categories"] == ["BACKEND"]
     assert call.kwargs["mode"] == "TECHNICAL"
     # maxQuestions is the session limit; initialQuestionCount controls this result.
     assert call.kwargs["max_questions"] == 2
@@ -133,7 +133,7 @@ async def test_consumer_skips_when_message_id_already_seen():
         {
             "sessionId": 99,
             "mode": "TECHNICAL",
-            "jobCategory": "BACKEND",
+            "jobCategories": ["BACKEND"],
             "documents": [],
             "maxQuestions": 3,
         }
@@ -161,7 +161,7 @@ async def test_consumer_defaults_initial_question_count_to_one():
         {
             "sessionId": 99,
             "mode": "TECHNICAL",
-            "jobCategory": "BACKEND",
+            "jobCategories": ["BACKEND"],
             "documents": [],
             "maxQuestions": 5,
         }
@@ -189,7 +189,7 @@ async def test_consumer_clamps_initial_question_count_to_at_least_one():
         {
             "sessionId": 99,
             "mode": "TECHNICAL",
-            "jobCategory": "BACKEND",
+            "jobCategories": ["BACKEND"],
             "documents": [],
             "initialQuestionCount": 0,
             "maxQuestions": 5,
@@ -233,7 +233,7 @@ async def test_consumer_injects_initial_rag_chunks_when_available():
         {
             "sessionId": 99,
             "mode": "TECHNICAL",
-            "jobCategory": "BACKEND",
+            "jobCategories": ["BACKEND"],
             "documents": [
                 {
                     "documentId": 1,
@@ -292,7 +292,7 @@ async def test_single_document_skips_rag_plan_mode():
         {
             "sessionId": 1,
             "mode": "TECHNICAL",
-            "jobCategory": "BACKEND",
+            "jobCategories": ["BACKEND"],
             "documents": [
                 {
                     "documentId": 1,
@@ -336,7 +336,7 @@ async def test_consumer_falls_back_to_document_context_when_rag_fails():
         {
             "sessionId": 99,
             "mode": "TECHNICAL",
-            "jobCategory": "BACKEND",
+            "jobCategories": ["BACKEND"],
             "documents": [
                 {
                     "documentId": 1,

backend/openapi.json

@@ -2515,9 +2515,13 @@
             "type" : "string",
             "enum" : [ "TECHNICAL", "PERSONALITY", "INTEGRATED" ]
           },
-          "jobCategory" : {
-            "type" : "string",
-            "enum" : [ "FRONTEND", "BACKEND", "INFRA", "DBA" ]
+          "jobCategories" : {
+            "type" : "array",
+            "items" : {
+              "type" : "string",
+              "enum" : [ "FRONTEND", "BACKEND", "INFRA", "DBA" ]
+            },
+            "minItems" : 1
           },
           "maxQuestions" : {
             "type" : "integer",
@@ -2549,7 +2553,7 @@
             }
           }
         },
-        "required" : [ "jobCategory", "mode" ]
+        "required" : [ "jobCategories", "mode" ]
       },
       "SessionResponse" : {
         "type" : "object",
@@ -2572,6 +2576,13 @@
             "type" : "string",
             "enum" : [ "FRONTEND", "BACKEND", "INFRA", "DBA" ]
           },
+          "jobCategories" : {
+            "type" : "array",
+            "items" : {
+              "type" : "string",
+              "enum" : [ "FRONTEND", "BACKEND", "INFRA", "DBA" ]
+            }
+          },
           "maxQuestions" : {
             "type" : "integer",
             "format" : "int32"

backend/src/main/java/com/stackup/stackup/session/application/SessionQuestionsRequester.java

@@ -68,7 +68,7 @@ public void onSessionCreated(SessionCreatedEvent event) {
         GenerateQuestionsPayload payload = new GenerateQuestionsPayload(
             event.sessionId(),
             event.mode(),
-            event.jobCategory(),
+            event.jobCategories(),
             documents,
             generalCount,
             event.maxQuestions(),

backend/src/main/java/com/stackup/stackup/session/application/SessionService.java

@@ -12,13 +12,15 @@
 import com.stackup.stackup.session.application.event.SessionEndedEvent;
 import com.stackup.stackup.session.domain.InterviewSession;
 import com.stackup.stackup.session.domain.InterviewSessionRepository;
+import com.stackup.stackup.session.domain.JobCategory;
 import com.stackup.stackup.session.domain.SessionContext;
 import com.stackup.stackup.session.domain.SessionContextRepository;
 import com.stackup.stackup.user.domain.User;
 import com.stackup.stackup.user.domain.UserRepository;
 import java.util.ArrayList;
 import java.util.LinkedHashSet;
 import java.util.List;
+import java.util.stream.Collectors;
 import lombok.RequiredArgsConstructor;
 import org.springframework.context.ApplicationEventPublisher;
 import org.springframework.data.domain.Page;
@@ -49,7 +51,7 @@ public SessionResult create(Long userId, SessionCreateCommand command) {
             title,
             command.memo(),
             command.mode(),
-            command.jobCategory(),
+            command.jobCategories(),
             command.maxQuestions(),
             command.maxDurationMinutes(),
             command.generalQuestionCount(),
@@ -63,7 +65,7 @@ public SessionResult create(Long userId, SessionCreateCommand command) {
             userId,
             session.getId(),
             session.getMode(),
-            session.getJobCategory(),
+            command.jobCategories(),
             session.getMaxQuestions(),
             session.getGeneralQuestionCount(),
             linkedIds
@@ -146,14 +148,17 @@ public SessionResult updateMeta(Long userId, Long sessionId, String title, Strin
         return SessionResult.of(session, contextDocumentIds(sessionId));
     }
 
-    // 제목 미입력 시 모드+직군으로 규칙 기반 제목 생성 (예: "백엔드 기술 면접").
+    // 제목 미입력 시 모드+직군으로 규칙 기반 제목 생성 (예: "프론트엔드·백엔드 기술 면접").
     // 히스토리에서 "면접 #id" 대신 의미 있는 제목을 보이게 한다.
     private String resolveTitle(SessionCreateCommand command) {
         String title = command.title();
         if (title != null && !title.isBlank()) {
             return title;
         }
-        return command.jobCategory().koreanLabel() + " " + command.mode().koreanLabel();
+        String jobs = command.jobCategories().stream()
+            .map(JobCategory::koreanLabel)
+            .collect(Collectors.joining("·"));
+        return jobs + " " + command.mode().koreanLabel();
     }
 
     private User loadUser(Long userId) {

backend/src/main/java/com/stackup/stackup/session/application/dto/GenerateQuestionsPayload.java

@@ -7,7 +7,7 @@
 public record GenerateQuestionsPayload(
     Long sessionId,
     SessionMode mode,
-    JobCategory jobCategory,
+    List<JobCategory> jobCategories,
     List<DocumentContext> documents,
     // Number of questions AI should generate for this initial callback.
     Integer initialQuestionCount,