fix(scout): BIS per-vacancy location and Confluent via the IBM careers API

BIS
- The RSS feed carries no location, so every vacancy was stamped with
  default_location "Basel, Switzerland". jr100491 (Hong Kong, BIS Asia office)
  therefore passed the CH filter and reached the 2026-10-14 triage.
- fetch_rss now resolves the location per item through _rss_item_location:
  the vacancy page's static "Geographical location" field
  (location_page_regex), then a "based in ..." sentence in the feed
  description, then default_location with a warning on stderr.
- Verified with --only=bis: 3 scraped, 2 eligible (both Basel); jr100491 now
  reads "8 Finance Street, Central, Hong Kong" and is excluded.

Confluent
- IBM closed the acquisition on 2026-03-17. The Ashby board dropped from 17
  jobs (2026-10-08) to {"jobs":[]} (2026-10-14), and careers.confluent.io is
  behind a Vercel bot checkpoint.
- New `ibm` adapter for the open IBM careers search API
  (www-api.ibm.com/search/api/v2; POST; size capped at 100, paged with
  `from`). Location is built from city, country and work mode, e.g.
  "United States - Remote".
- Confluent keeps its id, so seen-state and decisions still link. Verified
  with --only=confluent: 84 roles, none in CH/Europe-remote scope today, and no
  0-jobs warning.

CLAUDE.md corrections log: 2026-10-15 entry. Also notes that HashiCorp
(dropped 2026-06-06 for lacking a public API after the IBM acquisition) could
return through the same adapter.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

CLAUDE.md

@@ -183,6 +183,7 @@ _See `config.md` for user-specific corrections. Add verified errors here as you
 
 | Date | Correction | Files fixed |
 |------|-----------|-------------|
+| 2026-10-15 | **Two scout adapters were reporting wrong data without failing; both were found by the 2026-10-14 triage.** (a) **BIS:** the RSS adapter stamped `default_location: Basel, Switzerland` on every vacancy, so **jr100491 (Hong Kong, BIS Asia office)** passed the CH filter and reached a JD read. The feed carries no location, but each vacancy page has a static *Geographical location* field. `fetch_rss` now reads it per item (`location_page_regex`), falls back to a *"based in ..."* sentence in the feed description, and only then uses `default_location`, printing a warning when it does. Verified: Basel reqs still pass, and jr100491 now reads *8 Finance Street, Central, Hong Kong* and is excluded. (b) **Confluent:** IBM closed the acquisition on 2026-03-17, and the Ashby board went from 17 jobs (10-08) to `{"jobs":[]}` (10-14). careers.confluent.io sits behind a Vercel bot checkpoint. The roles are now IBM requisitions, served by the open IBM careers search API (`www-api.ibm.com/search/api/v2`, POST, `size` capped at 100, pages with `from`). New `ibm` adapter; Confluent keeps its id, so seen-state and decisions still link. First run: 84 roles, 0 in CH/Europe-remote scope. **HashiCorp was dropped on 2026-06-06 for having "no clean public ATS API" after IBM absorbed it. That API exists, so HashiCorp can come back through the same adapter if wanted.** **Rule: when an adapter must assume a field, the assumption has to be visible. A silent default looks exactly like real data.** | `scout.py` (`fetch_rss`, `_rss_item_location`, `fetch_ibm`, BIS and Confluent config) |
 | 2026-10-14 | **Spotfire was the sixth evidenced-but-unregistered skill, and junior mentoring was unrecorded - both surfaced by the BIS Basel jr100498 *Senior/Lead Data & Analytics Engineer* (MED IT) triage.** (a) **TIBCO Spotfire** sat in the BS-5 and BS-8 scopes (co-owned environment, technical Application Owner, C# extensions, TAF 2022, spatial wafer-data map charts) but not in the `skills` array, so the JD line *"using database reporting and business intelligence tools"* had no citable skill; registered `production-historical`, `allowed` on user instruction. It does not license Power BI, Tableau or Qlik. (b) The JD requires *"Experience providing general supervision and task-specific guidance to junior colleagues"*, and the only canonical evidence was BS-7 (students, one thesis as Zweitpruefer). User-confirmed: he **onboarded and mentored junior developers at Bosch and at Swisscom** - recorded as **BS-9** and **SW-10**, one per employer. The Swisscom phase (ART B2B or ART DPT) is not recorded, so write it in past tense. Neither is people management. (c) **SDMX: user-confirmed never used**; registered `forbidden` so the scanner catches it. It is an accountability line in the JD, not a qualification. (d) The same audit found **Teradata, Oracle Database and Hadoop/Impala** evidenced only in the SW-2/BS-2/BS-8 scopes and absent from the `skills` array, although every past skills line listed them; registered `production-historical` from those scopes (Oracle explicitly does not establish DBA work). **Lesson, same as 10-08: when a JD has a supervision or mentoring line, ask about junior colleagues before falling back on BS-7. Student supervision is weaker evidence and the stronger evidence was simply unrecorded.** | `claims.json` (BS-9, SW-10; skills TIBCO Spotfire, SDMX, Teradata, Oracle Database, Hadoop / Impala); `knowledge_base/extractions/2026-10-14_mentoring_spotfire_sdmx_clarification.md` |
 | 2026-10-08 | **Three more canonical gaps of the recurring shape, surfaced by the Kongsberg Seatex *Lead Engineer, DevOps and Test Infrastructure* (Trondheim) package.** (a) **Jenkins and GitLab CI/CD** were evidenced in claim scopes (GN-1, FC-1, BS-6, SW-3) but absent from the `skills` array, so no skills line could cite them; registered as `production-historical`, with GitLab keeping SW-3's "used, not built" limit. (b) **Embedded coursework** was unrecorded: user-confirmed an Embedded Systems course (C/C++ and VHDL with an ARM platform) and Robotics during his studies, and **no embedded work since** - recorded as **ED-1**, coursework-only, degree attribution not yet given. (c) **Current unit testing** was unrecorded: he writes unit tests today and knows pytest - recorded as **SW-9**; whether pytest is the Swisscom framework is not confirmed. The JD's required line *"Experience working with embedded SW and Linux"* stays a **half Gap** (hard-gate FAIL); the user overrode it knowingly. **Lesson, again: for any DevOps/test JD ask about current testing practice and about academic hardware work before scoring - neither lives in `claims.json` by default.** | `claims.json` (ED-1, SW-9, 7 skills); `knowledge_base/extractions/2026-10-08_embedded_coursework_testing_clarification.md`; Kongsberg package |
 | 2026-09-15 | **Swisscom was recorded as one undifferentiated current role, so past work read as present.** The first Geo Platform build said *"Own the ETL pipeline components"* and *"Owns ... Teradata"* in the summary - wrong. User-supplied: the tenure has two phases. **ART B2B** (first part, PAST): the legacy Teradata DWH - Fulfillment ETL component ownership (SW-2), Python on Kubernetes with GitLab CI/CD (SW-3), dashboards and analyses (SW-4), Kafka. **ART DPT, Team Offering** (CURRENT): migration and implementation of AWS data products on AWS, ODP-Flow, PySpark/Python, Glue, Iceberg, Athena, Airflow (SW-1, SW-6, SW-7). **Kafka and Kubernetes downgraded to `production-historical`**; SW-2/SW-3/SW-4 allowed verbs are now past tense; Apache Iceberg added as a canonical skill. Official internal title recorded: `Data, Analytics & AI Engineer IV` (III before Apr 2025), per the Oct 2025 Zwischenzeugnis. **The switch date is deliberately not recorded (user: not relevant) - never date the two units.** Any already-submitted package that presents Swisscom Kubernetes, Kafka or Teradata ownership as current stays as submitted history, but expect the question in interviews. **Lesson: the Zwischenzeugnis gives the whole tenure as one duty list, and a duty list says nothing about which duties are current - ask which phase each belongs to.** Same session, same shape: the Zeugnis's *"automation of CI/CD processes in GitLab"* overstated his part - the user clarified he **worked with** automated GitLab CI/CD rather than building it, and SW-3 now forbids claiming the automation. | `claims.json` (SWISSCOM org/title history; SW-1/2/3/4/6/7; Kafka, Kubernetes, Apache Iceberg; SW-3 CI/CD scope); `experience_swisscom.md` SW-3; Geo Platform resume |

job_scout/scout.py

@@ -254,7 +254,10 @@ COMPANIES = [
     # Dropped: ClickHouse (Glassdoor 3.3, 36% recommend, toxic-culture flag — 2026-05).
     # Dropped: HashiCorp — acquired by IBM (closed 2025); greenhouse/ashby/lever boards all 404,
     #          roles folded into IBM's careers (no clean public ATS API). 2026-06-06.
-    ("confluent", "Confluent", "ashby",      {"slug": "confluent", "_title_exclude": NOISE_TITLE_EXCLUDE}),
+    # Confluent: acquired by IBM (closed 2026-03-17). The Ashby board went empty (17 jobs on
+    # 2026-10-08, 0 on 2026-10-14); roles are now IBM requisitions. Moved to the `ibm`
+    # adapter 2026-10-15. Same id, so seen-state and decisions stay keyed to "confluent".
+    ("confluent", "Confluent (IBM)", "ibm",  {"query": "confluent", "_title_exclude": NOISE_TITLE_EXCLUDE}),
     ("gitlab",    "GitLab",    "greenhouse", {"board": "gitlab", "_title_exclude": NOISE_TITLE_EXCLUDE}),
     ("grafana",   "Grafana Labs","greenhouse",{"board": "grafanalabs", "_title_exclude": NOISE_TITLE_EXCLUDE}),
     # Added 2026-06-06 (Tier A/B data-infra). Databricks/Snowflake/Datadog have Zürich offices
@@ -369,6 +372,9 @@ COMPANIES = [
     # Low-volume RSS feed; no title filter (Innovation Hub roles can be oddly titled).
     ("bis",       "BIS (Basel)","rss", {
         "url": "https://www.bis.org/doclist/vacancies.rss",
+        # Each vacancy page has a static "Geographical location" sidebar field. BIS also
+        # hires for Hong Kong, Mexico City and other offices; see _rss_item_location.
+        "location_page_regex": r"Geographical location</h6>\s*<div[^>]*>\s*<p>([^<]+)</p>",
         "default_location": "Basel, Switzerland",
     }),
     # Dropped: Coinbase Ventures web3 talent network (Getro collection 1625) — 2026-08-18.
@@ -826,10 +832,37 @@ def fetch_smartrecruiters(args):
     return jobs
 
 
+def _rss_item_location(link, description, args):
+    """Per-item location for feeds that carry none.
+
+    Order: the item's own page via `location_page_regex` (first group), then a
+    "based in <place>" sentence in the feed description, then `default_location`.
+    Added 2026-10-15: stamping every BIS vacancy with default_location labelled a Hong Kong
+    req (jr100491) as Basel, so it passed the CH location filter and reached the triage.
+    """
+    pattern = args.get("location_page_regex")
+    if pattern and link:
+        try:
+            req = urllib.request.Request(link, headers={"User-Agent": USER_AGENT})
+            with urllib.request.urlopen(req, timeout=30, context=_ssl_context()) as resp:
+                page = resp.read().decode("utf-8", errors="replace")
+            match = re.search(pattern, page, re.I | re.S)
+            if match and match.group(1).strip():
+                return html.unescape(match.group(1).strip())
+        except (urllib.error.URLError, OSError, ValueError):
+            pass
+    match = re.search(r"\bbased in ([A-Z][^.;:]{2,60})", description)
+    if match:
+        return match.group(1).strip()
+    print(f"  ! {link or '?'}: no location on page or in feed, using default_location",
+          file=sys.stderr)
+    return args.get("default_location", "")
+
+
 def fetch_rss(args):
     """Generic RSS/RDF feed parser. BIS publishes vacancies as RSS 1.0 (RDF), whose
     <item> elements live in the http://purl.org/rss/1.0/ namespace. Falls back to plain
-    RSS 2.0 <item> elements. Location isn't in the feed, so default_location is required."""
+    RSS 2.0 <item> elements. Location isn't in the feed; see _rss_item_location."""
     import xml.etree.ElementTree as ET
     req = urllib.request.Request(args["url"], headers={"User-Agent": USER_AGENT})
     with urllib.request.urlopen(req, timeout=30, context=_ssl_context()) as resp:
@@ -844,13 +877,14 @@ def fetch_rss(args):
                 el = it.find(tag)
             return (el.text or "").strip() if el is not None and el.text else ""
         link = field("link")
+        description = re.sub(r"<[^>]+>", " ", field("description"))
         jobs.append({
             "id": link or field("title"),
             "title": field("title"),
-            "location": args.get("default_location", ""),
+            "location": _rss_item_location(link, description, args),
             "url": link,
             "posted": (it.findtext("dc:date", default="", namespaces=ns) or field("date")),
-            "description": re.sub(r"<[^>]+>", " ", field("description"))[:1500],
+            "description": description[:1500],
         })
     return jobs
 
@@ -1746,7 +1780,70 @@ def fetch_playwright(args):
     return jobs
 
 
+IBM_SEARCH_API = "https://www-api.ibm.com/search/api/v2"
+
+
+def fetch_ibm(args):
+    """IBM careers search: the open JSON endpoint behind ibm.com/careers/search.
+
+    Added 2026-10-15 for Confluent. IBM closed the acquisition on 2026-03-17, and the
+    Confluent Ashby board (`jobs.ashbyhq.com/confluent`) returns no jobs. Its roles are now
+    IBM requisitions, mostly titled "... - Confluent". careers.confluent.io sits behind a
+    Vercel bot checkpoint, so this API is the clean path.
+
+    `query` is a keyword search over title, description and body, as the site's own search
+    box sends it. The API rejects `size` above 100, so pages are fetched with `from`.
+    Location = city (unless "Multiple Cities" / "No City") + country + work mode, e.g.
+    "United States - Remote" or "Zurich, CH, Switzerland - Hybrid".
+    """
+    body = {
+        "appId": "careers", "scopes": ["careers2"], "lang": "zz", "size": 100,
+        "query": {"bool": {"must": [{"simple_query_string": {
+            "query": args["query"],
+            "fields": ["keywords^1", "body^1", "url^2", "description^2",
+                       "h1s_content^2", "title^3", "field_text_01"],
+        }}]}},
+        "sort": [{"_score": "desc"}],
+        "_source": ["title", "url", "description",
+                    "field_keyword_05", "field_keyword_17", "field_keyword_19"],
+    }
+    jobs, offset = [], 0
+    while True:
+        body["from"] = offset
+        req = urllib.request.Request(
+            IBM_SEARCH_API, data=json.dumps(body).encode("utf-8"), method="POST",
+            headers={"Content-Type": "application/json", "User-Agent": USER_AGENT})
+        with urllib.request.urlopen(req, timeout=30, context=_ssl_context()) as resp:
+            data = json.load(resp)
+        hits = data.get("hits", {}).get("hits", [])
+        for hit in hits:
+            src = hit.get("_source", {})
+            city = (src.get("field_keyword_19") or "").strip()
+            country = src.get("field_keyword_05") or ""
+            if isinstance(country, list):
+                country = ", ".join(country)
+            place = ", ".join(p for p in (
+                "" if city.lower().startswith(("multiple cities", "no city")) else city,
+                country.strip()) if p)
+            mode = (src.get("field_keyword_17") or "").strip()
+            url = src.get("url", "")
+            job_id = urllib.parse.parse_qs(urllib.parse.urlsplit(url).query).get("jobId", [""])[0]
+            jobs.append({
+                "id": job_id or url,
+                "title": (src.get("title") or "").strip(),
+                "location": f"{place} - {mode}" if mode else place,
+                "url": url,
+                "posted": "",
+                "description": (src.get("description") or "")[:1500],
+            })
+        total = data.get("hits", {}).get("total", {}).get("value", 0)
+        offset += len(hits)
+        if not hits or offset >= total or offset >= 1000:
+            return jobs
+
+
 ADAPTERS = {
+    "ibm": fetch_ibm,
     "workday": fetch_workday,
     "ashby": fetch_ashby,
     "greenhouse": fetch_greenhouse,
@@ -2613,7 +2710,8 @@ def _main():
 #
 # Automated (COMPANIES above):
 #   workday        nvidia, novartis, equinor (norway_only)
-#   ashby          kraken, openai, confluent, snowflake
+#   ashby          kraken, openai, snowflake
+#   ibm            confluent (IBM careers search API since 2026-10-15; Ashby board empty)
 #   greenhouse     anthropic, gitlab, grafana, databricks, datadog, elastic, fivetran
 #   pcsx           microsoft
 #   smartrecruiters metgroup, cern