feat(ruag): submit AI Engineer C5I, and record the Kdo Cy package

RUAG C5I - AI Engineer C5I (Thun, app ID 18027): SUBMITTED 2026-08-27.
Evidence Fit 74/100, fit class Stretch, title-capability hard gate FAIL
(R1 build/operate the AI-LLM platform and R2 in-house LLM/retrieval are
Adjacent, not Direct) - all knowingly accepted under the user's explicit
Phase 0 override. Consumes the cohort's sole Stretch slot: cohort is now
6/10, Stretch 1/1.

Critique ran twice. Round 1 scored the documents 85/100 and raised three
Tier 1 items; Round 2, after the fixes, scores 93/100 with truth and
provenance 24/25 and zero Tier 1 findings. Evidence Fit did not move and
was not allowed to: PP-3 is a personal project and cannot convert an
Adjacent title-capability into a Direct one.

Documents (.tex is the deliverable; PDFs are gitignored):
- resume 2pp/13 bullets, letter 1pp/295 words, both validators PASS
- headline is now the canonical title "Staff Data, Analytics & AI
  Engineer", which puts the req's own word above the fold
- PP-3 added as a Projekte section - the only current Linux/hardening
  evidence, since BS-6 ended Dec 2022
- the letter names the AI-platform gap in one sentence, then connects
  SW-5 to C5I's stated DevSecOps model
- "governte" -> "governance-konforme"; JD term coverage 18/22 -> 22/22
  claimable, with all six gap terms still correctly absent

Two defects found and fixed that the first critique missed:
- the resume never loaded babel, so a German document was hyphenated
  with English patterns (Hal-bleiterfertigung, Tran-skription). Fixed
  with babel[ngerman] plus a Transkription exception; this also cleared
  an overfull box. Check this on every future German package -
  resume_template.tex likely has the same omission.
- IBM AI Engineering had no primary-source record. Certificate read
  directly (IBM via Coursera, 4 Jun 2020, verify 3ZBZFVAL6A34), recorded
  as entry #8; it also proves PyTorch, now evidence: certification.

Also included: the submitted Kdo Cy DevOps Engineer III package, the
Capgemini omit rule promoted into config.md, BW-1 canonicalized in
experience_bundeswehr.md, and a scout.py comment correcting the
telenorgroup slug from "near-empty" to a claimed board serving stale
phantom listings that DEMO_TITLES would not catch.

Compensation, PSP/project eligibility and role level were never resolved
before sending and are now live screening topics.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01JMcHCsTKWvVzqyLChF5ckk

knowledge_base/extractions/thiessen_certifications.md

@@ -1,7 +1,7 @@
 # Dennis Thiessen — Certifications Extraction
 
 > One file for all cert PDFs. Added as each cert is processed.
-> Last updated: 2026-03-28
+> Last updated: 2026-08-27
 
 ---
 
@@ -16,6 +16,7 @@
 | 5 | Projektleiter Baustein A/IT — Das IT-Projektmanagement (seminar) | Integrata AG | 1–5 Sep 2014 | N/A | Seminar-Nr. 2113 | 5-day attendance (Teilnahmebestätigung). NOT a cert — do not list on resume/CV. Topics: IT project planning, control, risk analysis. Context: during Bundeswehr period. |
 | 6 | AI for Trading Nanodegree | Udacity (co-created with WorldQuant) | 13 May 2021 | N/A | confirm.udacity.com/DJ9QTAH9 | Quantitative finance + ML for trading; completed during Bosch period. Relevant for quant/fintech roles; niche signal for blockchain/crypto interest. |
 | 7 | AWS Certified Solutions Architect – Associate | Amazon Web Services (via Alpine Testing / CertMetrics) | 26 Sep 2024 | 26 Sep 2027 (active) | cp.certmetrics.com/amazon — verified 2026-03-27 | ACTIVE. High-value cert for Data Platform / Infra and Staff Data Engineer roles. Pairs well with Udacity DataEng AWS nanodegree. |
+| 8 | IBM AI Engineering (Professional Certificate, 6 courses) | IBM via Coursera | 4 Jun 2020 | N/A (no expiry) | coursera.org/verify/professional-cert/3ZBZFVAL6A34 | Name: "Dennis Thießen" (ß variant). **Verified against the certificate PDF 2026-08-27** (`C:\myCloud\Bewerbungsunterlagen\Zeugnisse\Zertifikate\cert_IBM_AI_Engineering.pdf`). Courses: Machine Learning with Python; Scalable ML on Big Data with Apache Spark; Intro to Deep Learning & Neural Networks with Keras; Deep Neural Networks with **PyTorch**; Building Deep Learning Models with **TensorFlow**; AI Capstone Project with Deep Learning. This is the source of the `TensorFlow/Keras` **and** `PyTorch` entries in `claims.json` — both stay `certification-context-only`. Explicitly non-credit: the certificate states it confers no grade, course credit or degree, so never present it as an academic qualification. |
 
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