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chore(applications): archive BIS + NATO submitted packages, ignore tmp/

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Add BIS Basel and NATO JWC Stavanger application output (resume/CV, cover letter,
session file, critique) plus the Bundeswehr experience file backing the NATO
package; update session status tables in AGENTS.md/CLAUDE.md; record two new
Bash allowlist entries for the job scout venv. tmp/ is scratch working files,
now gitignored.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
This commit is contained in:
dennisthiessen
2026-07-18 21:03:45 +02:00
co-authored by Claude Sonnet 5
parent 3ad39117d6
commit d0525cc437
18 changed files with 1766 additions and 1 deletions
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resume_builder/experience/experience_bundeswehr.md
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# Experience: Officer — German Armed Forces (Bundeswehr)
## July 2008 – November 2014 | Germany
### Cross-Position Section
**Source:** User confirmation (2026-07-10); thiessen_linkedin_profile.md
**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.
### Achievement BW-1: Officer Training and Service
**User's role:** Officer candidate / officer
**Status:** Completed service; resigned as Second Lieutenant
**Context:** Completed officer candidate training and officer school, then served in the German Armed Forces for six years.
**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.
**ATS keywords:** German Armed Forces, Bundeswehr, officer, multinational environment, operational context, structured leadership
**Reframing notes:**
- Defence / NATO roles: Include as concise context for operational judgement and organisational familiarity.
- All other roles: Omit or retain only as an additional-information line.
- Accuracy: State only verified training, service duration and rank.
resume_builder/experience/experience_swisscom.md
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---
### Achievement SW-8: Domain-Grounded LLM Agents for Q&A and Task Assistance
**Source:** User-confirmed current Swisscom work (2026-07-10)
**User's role:** Creator / configurator of the agents in a Swisscom-owned web interface
**Status:** Models are selectable in the web interface. Deployment, adoption, API and retrieval implementation are not known — do not call production deployment, fine-tuning, RAG, hybrid search, API engineering, or broader agentic-system ownership without further evidence.
**Context:** Dennis configured LLM agents in a Swisscom-owned web interface, selecting from available models and supplying a domain-specific knowledge base for question answering and domain tasks, including migration assistance and data mapping. This is direct hands-on LLM application configuration, distinct from model training, fine-tuning or API-level deployment.
**Safe bullet direction:** Configured domain-grounded LLM agents in a Swisscom-owned web interface, selecting available models and supplying a knowledge base for Q&A, migration assistance and data mapping. Add only verified adoption, API or retrieval details.
**Key skills:** LLM application configuration, model selection, AI agents, domain knowledge bases, question answering, migration assistance, data mapping
**ATS keywords:** LLM-powered applications, AI agents, model selection, knowledge grounding, question answering, workflow automation, data mapping
**Reframing notes:**
- ML/AI: HIGH for LLM-specific roles; lead with applied LLM delivery, then connect reliable data foundations and evaluation discipline.
- Accuracy: Never say “trained an LLM” unless model weights were fine-tuned. Prefer “grounded,” “configured,” or “provided with a domain-specific knowledge base.”
- Production: Use “internal” or “prototype” only if true; otherwise omit deployment-status language until verified.
---
## Position Summary
| Achievement | ID | Priority for DE | Priority for Analytics | Priority for ML/AI | Priority for Platform |
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| Security Champion | SW-5 | MED | LOW | MED | HIGH |
| PySpark | SW-6 | MED | LOW | MED | MED |
| Data Mesh / Data Products / Metadata (agentic foundation) | SW-7 | HIGH | MED | HIGH | HIGH |
| Domain-Grounded LLM Agents | SW-8 | MED | LOW | HIGH | MED |