dennisthiessenandClaude Opus 5
a0f844c143
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
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30 lines
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Markdown
# Experience: Officer — German Armed Forces (Bundeswehr)
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## July 2008 – November 2014 | Germany
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### Cross-Position Section
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**Source:** User confirmation (2026-07-10); thiessen_linkedin_profile.md
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**Career arc framing:** Dennis completed the officer candidate course and officer school during six years in the German Armed Forces, leaving service as Second Lieutenant. This is relevant to NATO and defence roles as authentic operational and organisational context. It was not a technical AI or NATO civilian role, and no current or former clearance should be inferred.
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### Achievement BW-1: Officer Training and Service
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**Canonical ID:** BW-1
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**Last verified:** 2026-08-27
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**User's role:** Officer candidate / officer
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**Status:** Completed service; resigned as Second Lieutenant
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**Ownership scope:** Individual service and completed training. No command scope, deployment or technical military responsibility is established.
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**Verified result / metric state:** Six years of service and separation as Second Lieutenant are verified; no performance metric is established.
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**Context:** Completed officer candidate training and officer school, then served in the German Armed Forces for six years.
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**Safe bullet direction:** Completed officer candidate training and officer school during six years in the German Armed Forces (Bundeswehr), leaving service as Second Lieutenant. Do not imply a current clearance, NATO service, combat role, technical AI work, or responsibilities not verified.
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**ATS keywords:** German Armed Forces, Bundeswehr, officer, multinational environment, operational context, structured leadership
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**Relevant role context:** Defence, military and public-security employers; organisational familiarity rather than technical evidence.
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**Reframing notes:**
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- Defence / NATO roles: Include as concise context for operational judgement and organisational familiarity.
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- All other roles: Omit or retain only as an additional-information line.
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- Accuracy: State only verified training, service duration and rank.
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