# Session: Microsoft — Principal Forward Deployed Engineer, Software Engineer (German Speaking)

## JD Info
- **File:** `output/Microsoft_Principal_FDE_SWE/JD_microsoft_principal_fde_swe.txt`
- **JD source:** live scrape 2026-07-27 via Playwright (job_scout venv, `apply.careers.microsoft.com` position page) — **real posting text, verbatim**
- **Role:** Principal Forward Deployed Engineer – Software Engineer – German Speaking
- **Req:** 200043897 · posted 2026-07-17 · open min. 5 days, ongoing until filled
- **Company:** Microsoft — **Frontier Company Engineering** (new org, formalized 2026-07-02)
- **Location:** Switzerland, Zürich — **work site "0 days / week in-office – remote"**
- **Travel:** header says 25–50%; preferred quals say "comfortable with travel up to 25%" (tension — clarify at screen)
- **Role type:** Individual Contributor (JD: "This is a senior individual contributor role")
- **Bundle:** PRIMARY `bundle_data_engineer.md` (Tier 1) + SECONDARY `bundle_ml_ai_engineer.md` (Tier 2) — pending user confirm
- **Format:** Resume (2-page, resume.cls) + 1-page cover letter
- **Salary:** IC4 CHF 146,200–245,900 · **IC5 CHF 183,800–309,700** (IC5 floor clears the 180k all-in bar)

## JD Analysis

### Requirements
| # | Requirement | Match | Evidence |
|---|-------------|-------|----------|
| 1 | BSc CS or related + 6+ yrs coding (C/C++/C#/Java/JS/Python) | **Direct** | M.Eng. Computer Aided Engineering (Software Design & Engineering), UniBw München; ~12 yrs since 2013. Python/Java core; C# at Fraunhofer/Bosch (secondary) |
| 2 | Preferred: MSc + 8+ yrs / BSc + 10+ yrs | **Direct** | M.Eng. 2013 + ~12 yrs — clears the strongest preferred tier |
| 3 | Partnering directly with customers or internal stakeholders, end-to-end delivery | **Direct** | SW-4 B2B data products for stakeholders; BS-3 Application Owner (vendor mgmt, training, SLOs); GN-1 |
| 4 | Build and ship production-grade solutions, end-to-end ownership | **Direct** | SW-2 Component Owner under on-call SLA; SW-3 K8s + GitLab CI/CD; BS-1 ML inference into 24/7 fab |
| 5 | Engineering execution in complex/ambiguous, fast-moving environments | **Direct** | BS-1 (24/7 fab, no deployment windows) is the strongest constraint story in the KB |
| 6 | Engage/influence senior stakeholders, guide technical + business decisions | **Bridge (med-high)** | SW-4 stakeholder/product interface, BS-3 Application Owner, Swisscom Leadership Cohort 2025, Bundeswehr officer service. Not a formal "trusted advisor to C-suite" track record |
| 7 | Hands-on AI solution delivery — **building/deploying LLM-based systems**, model quality/performance, modern cloud AI platforms | **Bridge (LOW-MED) — KEY RISK** | SW-8 = *configured* domain-grounded LLM agents in a Swisscom web interface (model selection + knowledge base) for Q&A/migration/data-mapping. **Deployment, adoption, RAG, API and eval work are NOT verified.** SW-7 Data Mesh/metadata = the data foundation agents query |
| 8 | Apply industry/customer context to tailor solutions | **Direct** | Telco (Swisscom), semiconductor (Bosch), insurance (Generali), broadcast (Vizrt), defence (Bundeswehr) — genuine multi-industry range |
| 9 | Prepare/transition work to FDE crews, continuity across engagement lifecycle | **Bridge (med)** | BS-3 Application Owner: documentation, training, vendor management, handover |
| 10 | Entrepreneurial mindset, drive urgency and accountability | **Bridge (med)** | On-call SLA ownership, proactive process automation (SW-4), promotion arc |
| 11 | **Must speak fluent German** | **Direct — DIFFERENTIATOR** | German native speaker (German citizen). Narrows the CH candidate pool hard at Principal level |
| 12 | Travel 25–50% | **Direct** | Lived/worked NO/DE/CH + Shanghai master's; travel-OK from Bern (no relocation) |

### ATS Keywords
- **Role/lane:** Forward Deployed Engineer, FDE, customer-embedded, production-grade, end-to-end ownership, individual contributor, principal
- **AI/LLM:** LLM-based systems, AI agents, domain-grounded, knowledge base, cloud AI platforms, agentic workflows, model selection
- **Engineering:** Python, Java, C#, Kubernetes, Docker, CI/CD (GitLab), microservices, containerization, DevOps
- **Data/cloud:** AWS (S3, Glue, Athena, Iceberg, Redshift, Airflow, CloudFormation), Kafka, Teradata, Oracle, Data Mesh, data products, metadata management, ETL
- **Delivery/soft:** stakeholder engagement, technical leadership, ambiguity, time to value, SLA, on-call, agile, handover/enablement
- **Language:** German (native), English (fluent)

### Gap Assessment
- **Direct:** coding breadth + tenure, production ownership under SLA, K8s/CI/CD delivery, multi-industry context, German, travel/mobility, cloud (AWS)
- **Bridge (state honestly):**
  - Senior-stakeholder influence — real but not a C-suite advisory track record (med-high)
  - FDE-crew handover — Application Owner handover/training is the analogue (med)
- **Gap (do NOT claim):**
  - **Azure.** His cloud depth is **AWS**, not Azure/Foundry/Copilot Studio. The JD does not name Azure, but the org is Azure-centric. Do not invent Azure experience; position AWS as transferable cloud-native depth and let German + delivery carry the file.
  - **Deep LLM engineering.** No fine-tuning, no RAG/eval pipeline ownership, no LLM serving infrastructure. SW-8 is configuration-level. Never write "built/deployed LLM systems in production."
  - No consulting/professional-services or pre-sales title.
  - No formal people management (JD does not ask for it — this is an IC role, so not a gap for this req).

## Company Context
- **Mission:** "Empower every person and every organization on the planet to achieve more."
- **Microsoft Frontier Company** — formalized **2026-07-02**: ~$2.5B and ~6,000 industry + engineering specialists dedicated to deploying enterprise AI (Azure, Copilot, agents, customer data) directly inside customer organizations. Named early customers include Unilever and Novo Nordisk. This req (posted 15 days later) is part of that build-out — a newly funded org hiring at volume, which materially improves odds versus a single backfill req.
- **This role:** primary technical leader aligned to one strategic account; ships production solutions inside the customer's environment "in days, not months," then hands off to FDE crews. Microsoft is now selling *implementation* as the product — the bottleneck is enterprise data readiness and integration, not model quality.
- **Swiss context:** Microsoft AI Tour Zürich (2026-04-29, 3,000+ leaders at Messe Zürich) themed on AI moving from experimentation to production; Microsoft targets 1M people in Switzerland skilled in AI/digital by 2027 (500k+ done). German-speaking DACH enterprise accounts are the obvious deployment ground for this Zürich req.
- **Culture:** growth mindset, respect/integrity/accountability; FDE sub-culture prizes speed, ambiguity tolerance, and hands-on shipping over advisory decks.
- **"Why them" angle:** Frontier's stated problem — enterprise AI stalls on messy, ungoverned data and integration reality, not on models — is exactly the problem Dennis works on now (Data Mesh, governed data products, metadata management as the foundation agents query). He has been on the *customer* side of this equation inside a large regulated European enterprise.

## Framing Strategy
- **Lead narrative:** *A senior engineer who ships production systems inside large, regulated European enterprises — and who has built the governed data foundation that enterprise AI actually needs — now bringing that from the inside of Swisscom/Bosch to Microsoft's customers, in German.*
- **Reframing map:**
  - Component Owner (Fulfillment ETL, on-call SLA) → end-to-end ownership of production-grade solutions
  - B2B data products + stakeholder analytics → partnering directly with customers to translate business needs into technical approaches
  - Bosch ML inference into 24/7 fab → shipping into an unforgiving live customer environment, no deployment window
  - Application Owner (SLOs, vendor mgmt, training, documentation) → engagement continuity and handover to delivery crews
  - Data Mesh / data products / metadata management → the governed, discoverable data layer enterprise AI and agentic workflows depend on
  - Multi-industry career (telco, semiconductor, insurance, broadcast, defence) → applying industry context to tailor solutions
- **Emphasize:** production ownership under SLA · shipping into constrained live environments · multi-industry range · German + international mobility · cloud-native (AWS) depth · the data-foundation-for-AI angle
- **Downplay:** test automation / BDD / QA early career · RPA/Camunda · Spotfire/BI tooling · academic framing · Security Champion (JD does not ask for security)
- **CL hooks:** (1) Frontier Company launch 2026-07-02 and "implementation as the product"; (2) Bosch 24/7 fab ML deployment as the ship-into-live-environment credential; (3) Data Mesh/metadata as the enterprise-AI-readiness answer; (4) German-language DACH delivery from Bern.
- **User directives:** none given beyond role selection.

### Scope Discipline guardrails (CLAUDE.md + `[[feedback_bigcorp_ownership_scope]]`)
The KB itself contains framings that violate the scope rule — **do not copy them verbatim**:
- `bundle_data_engineer.md` S3/S5 and `experience_swisscom.md` SW-1 say "Led migration of legacy Teradata/Oracle ETL stack" / "sole technical lead." Scope it: *"migrated my domains' ETL stack to AWS"* / *"contributed to the warehouse migration."*
- SW-7 2L opens "Built decentralized Data Mesh" — banned pairing. Use *"Built governed data products within Swisscom's company-wide Data Mesh."*
- SW-8: never escalate "configured" to "built/deployed/fine-tuned."

## Critique Context
- **Reviewer persona:** A Microsoft Frontier FDE hiring manager or Principal FDE peer in Zürich — ships customer code weekly, has watched enterprise AI pilots die on data access and integration. Impressed by: evidence you have personally carried something into a hostile production environment and owned the pager; concrete stakeholder translation. Bored by: tool lists, certification stacking, "passionate about AI," advisory language with no shipping evidence.
- **Competitive landscape:** The obvious fit is a Big-4 / Accenture / Microsoft-partner consultant with Azure + Copilot Studio delivery scars and German, or an ex-Palantir FDE. Versus them Dennis is short on Azure and on customer-facing delivery *titles* — but longer on genuine production ownership inside an enterprise (they usually leave before the pager) and on the data-governance layer Frontier keeps hitting. Play the insider-operator card, not the consultant card.
- **Domain vocabulary (insider vs outsider):** "time to value," "engagement lifecycle," "crew handover," "account-aligned," "shipping in days not months," "data readiness," "grounding," "agent orchestration." Outsider tells: calling FDE work "consulting," saying "solutioning," implying pre-sales, or overclaiming LLM internals.

## Cover Letter Plan
- **Institution type:** Industry — hyperscaler, new customer-embedded engineering org
- **Paragraph count:** 4 paragraphs, 250–300 words, 1 page
- **P1 hook:** Frontier Company (launched 2026-07-02) sells implementation as the product; the failure mode is enterprise data readiness. Open with Bosch: containerized ML inference into a 24/7 wafer fab with no deployment window — shipping into a live environment that cannot be paused.
- **P2–P3 evidence:** SW-2 Component Owner under on-call SLA + SW-3 K8s/GitLab CI/CD (production ownership); SW-7 Data Mesh/governed data products/metadata (the AI-readiness layer); SW-4 + BS-3 (stakeholder translation, handover, training).
- **Domain pivot:** From building the data foundation *inside* one enterprise → doing it *alongside* many, as an account-aligned FDE. One honest sentence on LLM work at configuration level; no overclaim.
- **Jargon level:** Technical (engineer-to-engineer), HR-safe on the German/mobility lines.
- **"Why them" hook:** German-language delivery to DACH enterprises from Bern, plus the Swiss-market push (AI Tour Zürich, 1M-skilled-by-2027) — and a career spent on exactly the data problems Frontier's customers are stuck on.

### CL as-built (2026-07-27) — hooks verified
P1 hook was **changed from the session plan**: instead of opening on the Frontier launch facts ($2.5B / 6,000 engineers / 2026-07-02), the letter opens on **Microsoft's own stated premise** — enterprise AI fails on making models useful inside a real company, not on model access. Launch-stat recitation reads as press-release paraphrase; the premise framing turns Dennis's weakest area (LLM depth) into the letter's argument (data readiness is the bottleneck, and that is his day job). The MIT Project NANDA "95% of GenAI pilots deliver zero P&L impact" stat behind this framing was **deliberately not quoted** — an unsourced number in a CL invites a fact-check.

**Deliberate avoidance:** Microsoft publicly distanced itself from the FDE label at launch ("This goes beyond what has been labeled as Forward-Deployed Engineering"), even though the req title uses it. The CL therefore uses the JD's own vocabulary but never argues FDE-as-a-category.

**Hook verification:**
| Claim | Evidence | Source |
|---|---|---|
| Frontier Company premise: hard part is making models useful inside real companies, not model access | Verified. $2.5B / ~6,000 engineers, announced 2026-07-02 by Judson Althoff, president Rodrigo Kede Lima. Early partners Unilever, Land O'Lakes, Novo Nordisk. Framing tied to MIT Project NANDA finding that 95% of enterprise GenAI pilots show zero P&L impact | [TechCrunch](https://techcrunch.com/2026/07/02/microsoft-launches-its-own-ai-deployment-company-with-2-5-billion-commitment/), [GeekWire](https://www.geekwire.com/2026/microsoft-announces-2-5b-frontier-company-to-embed-ai-engineers-inside-customers/), [CIO Dive](https://www.ciodive.com/news/microsoft-25b-embed-engineers/824392/) |
| AI Tour Zürich, April 2026 | Verified: 2026-04-29, 3,000+ leaders at Messe Zürich, themed on AI moving from experimentation to deployment | [Microsoft Source EMEA](https://news.microsoft.com/source/emea/2026/04/microsoft-ai-tour-zurich-setting-direction-in-the-ai-era/) |
| One million people in Switzerland skilled by 2027 | Verified; 500,000+ already skilled | [Microsoft Source EMEA](https://news.microsoft.com/source/emea/features/switzerlands-digital-future-microsofts-commitment/) |

**ISE differentiation (2nd live MS Zürich application):** different hook (Frontier data-readiness vs. ISE Engineering Fundamentals Playbook), no cross-industry ramp list, and the $400M Swiss datacenter line was **not reused** (AI Tour / skilling used instead).

**One CL-only claim, not on the resume:** Generali posted him to Cologne and Vienna for months at a time. Held back from the resume line deliberately (session line 146) and used here to evidence the 25–50% travel requirement.

## Bullet Plan

**Confirmed Phase 0 decisions:** bundle = Data Engineer PRIMARY + ML/AI SECONDARY · LLM framing = hedge tightly, lead with data foundation · format = 2-page resume + 1-page CL.

### Budget decision — RESOLVED (user-confirmed 2026-07-27)
`resume_reference.md` Quick Budget Card says **~20 variable bullets**; `bundle_data_engineer.md` says **9–11**. They disagree.

**Resolution: 12 bullets / 20 rendered lines, mixed 2L+1L weights**, chosen for clarity over density on user instruction.

Readability research behind the call:
- [Ladders eye-tracking](https://www.theladders.com/static/images/basicSite/pdfs/TheLadders-EyeTracking-StudyC2.pdf): 7.4 s initial scan; resumes fail on "cluttered layouts, a lack of white space… and long sentences." Adequate white space *looks* longer to scan but is absorbed faster.
- Consensus density: **3–6 bullets per job**, tapering by recency (current 4–6 → oldest 2–3); recruiters skim past the 6th–7th bullet in a block.
- Recommended bullet length: **15–25 words**. A 2L bullet at ~200 chars is ~30 words — above range. This, not the count, was the source of the "packed" feeling.

**Applied:** 2L kept where substance earns it (Swisscom, Bosch); 1L for the three older positions. `config.md`'s "all variable bullets are 2L" is **overridden for this package only** — user declined a global config change.

### Position 1 — Swisscom, Staff Data, Analytics & AI Engineer (Oct 2023 – Present) — 5 bullets, 10 lines
| | ID | Achievement | Variant | Lines | JD Match |
|---|---|---|---|---|---|
| * | SW-2 | Component Owner, Fulfillment ETL — on-call SLA, governance | 2L | 2 | Direct (req 4) — LEAD |
| * | SW-7 | Governed data products + metadata mgmt within Swisscom's Data Mesh (AWS) | 2L | 2 | Direct (req 7 data-readiness) |
| * | SW-1 | Migrated **his domains'** ETL stack to AWS (S3/Glue/Athena-Iceberg/Redshift/Airflow/CFN) | 2L | 2 | Direct |
| * | SW-4 | B2B data products + stakeholder delivery, automation, RCA | 2L | 2 | Direct (req 3 — REQUIRED qual) |
| * | SW-8 | Configured domain-grounded LLM agents (model selection + knowledge base) | 2L | 2 | Bridge LOW-MED (req 7) — HEDGED |
| o | SW-3 | Python data apps on Kubernetes + GitLab CI/CD | 2L | 2 | **CUT for density** — K8s/Docker still carried by BS-1 + Skills; SW-4 kept instead because req 3 is a *required* qual |
| o | SW-6 | PySpark | — | — | Fold into Skills |
| x | SW-5 | Security Champion | — | — | JD silent on security; corrected to 2025/2026 team role, default OMIT |

### Position 2 — Bosch Semiconductor Dresden, (Senior) Data Engineer (Feb 2020 – Dec 2022) — 3 bullets, 6 lines
| | ID | Achievement | Variant | Lines | JD Match |
|---|---|---|---|---|---|
| * | BS-1 | Containerized ML inference (Docker/K8s/Ansible) into 24/7 fab | 2L | 2 | Direct (req 5) — LEAD |
| * | BS-3 | Application Owner — SLOs, vendor mgmt, training, documentation | 2L | 2 | Direct (req 9 handover, req 6) |
| * | BS-2 | Data services in Python, Java and C# over Oracle + Hadoop/Impala | 2L | 2 | Direct (req 1 languages) |
| o | BS-4 | ELK + Kafka anomaly-detection PoC, Grafana/Prometheus/Loki | 2L | 2 | Filler — platform breadth |
| o | BS-5 | Spotfire platform co-ownership + TIBCO Analytics Forum 2022 talk | 2L | 2 | Filler — public speaking credential |

### Position 3 — Fraunhofer CML Hamburg, Research Software Engineer (Sep 2018 – Oct 2019) — 2 bullets, 2 lines
| | ID | Achievement | Variant | Lines | JD Match |
|---|---|---|---|---|---|
| * | FC-1 | SCEDAS (C#/.NET/MS SQL) + independently established Jenkins CI/CD | **1L** | 1 | Direct (req 1 C#) |
| * | FC-3 | MISSION microservices (Express.js, JavaScript, Docker, SQLite) | **1L** | 1 | Direct (req 1 JS) |
| o | FC-2 | ARTUS ML/NLP for sea-rescue transcription — verb MUST be "Contributed" | 1L | 1 | Reserve — honest ML thread |

### Position 4 — Vizrt Bergen (Norway), DevOps Engineer (Jul 2017 – May 2018) — 1 bullet, 1 line
| | ID | Achievement | Variant | Lines | JD Match |
|---|---|---|---|---|---|
| * | VZ-1 | Python + C++ distributed video transcoding backend (CNN, BBC, Al Jazeera) | **1L** | 1 | Direct (req 1 C++; international) |
| o | VZ-2 | A/V test suite + CI/CD quality gates | 1L | 1 | Reserve |

### Position 5 — Generali GDIS **Hamburg**, Software Engineer → IT Consultant (May 2015 – Jun 2017) — 1 bullet, 1 line
_Location line reads **Hamburg, Germany** — user-confirmed 2026-07-27. **Cologne and Vienna were international-traineeship stations** (several months each), NOT the base. Omitted from the resume line as noise; **held as a cover-letter / interview asset** since this JD wants 25–50% travel and international delivery. See `[[feedback_generali_location]]`._
| | ID | Achievement | Variant | Lines | JD Match |
|---|---|---|---|---|---|
| * | GN-1 | Introduced BDD + held technical ownership; trained team, Java Community talk | **1L** | 1 | Bridge (req 9 enablement, initiative) |
| o | GN-3 | Java/J2EE features, XLDeploy, Apache Camel/Spring Boot PoC | 1L | 1 | Reserve (req 1 Java) |
| x | GN-2 | UIPath RPA | — | — | Off-thesis |

**Budget:** **12 bullets / 20 rendered lines** (Swisscom 5×2L, Bosch 3×2L, Fraunhofer 2×1L, Vizrt 1×1L, Generali 1×1L).
Reserve if page 2 underfills, in priority order: **SW-3** (K8s/CI-CD, 2L) → **BS-4** (ELK PoC, 2L) → **FC-2** (ARTUS, 1L) → **VZ-2** (1L) → **GN-3** (1L) → **BS-5** (Spotfire/TAF 2022, 2L).
Rule: if underfilled, **add a reserve bullet — never inflate an existing one past ~205 chars.**
**Excluded per provenance/config:** SW-5 (Security Champion — config conflict + not asked), GN-2/GN-4, CA-1 (Capgemini — excluded per `[[user_profile]]`), FC-4.
**Position themes to generate:** each rSubsection theme must carry the FDE narrative (ownership → delivery → enablement), not generic data-engineering labels.

## Output Files
- Resume: `output/Microsoft_Principal_FDE_SWE/e2e_microsoft_principal_fde_swe_resume.tex`
- Cover Letter: `output/Microsoft_Principal_FDE_SWE/e2e_microsoft_principal_fde_swe_cover_letter.tex`
- Critique: `output/Microsoft_Principal_FDE_SWE/critique_microsoft_principal_fde_swe.md`

## Edit 1 Baseline
- Pages: 2
- Char violations: none (18 variable experience bullets; 5 fixed certification items excluded)
- Orphan violations: none
- White space last page: roughly the lower quarter-to-third (about 12--14 rendered lines)
- Variable bullets: 18
- Rendered lines: 29
- Status: COMPLETE

## Edit History
### Edit 1 (2026-07-27): Tier 1 critique fixes, Option A
- Changes: corrected Skills provenance; added Forward Deployed Engineering as future intent; surfaced the Apr 2025 Senior-to-Staff promotion; strengthened business-needs and transition vocabulary; rewrote the CL opener around Bosch/Swisscom production proof.
- Source: critique Tier 1 items 1, 2 and 4 plus Tier 2 vocabulary items 1--2; user-approved Option A retained the mixed 1L/2L structure.
- Verification: resume 2 pages; CL 1 page and 262 words; 0 OVER bullets; 0 orphan violations; 0 box warnings; fingerprint scan passed.
- Layout decision: page-2 white space remains intentional under Option A; template-locked typography and spacing were not changed.

| Metric | Before | After | Delta |
|---|---:|---:|---:|
| Page count | 2 | 2 | 0 |
| Char violations | 0 | 0 | 0 |
| Orphans | 0 | 0 | 0 |
| White space | lower quarter-to-third | unchanged, accepted | 0 |
| Variable bullets | 18 | 18 | 0 |
| Rendered lines | 29 | 29 | 0 |

## Critique Summary
- **Pass 2 critique score:** **84.2/100** (2026-07-27; CURRENT), up from 80.8 after Edit 1.
- **Interview estimate:** 45--55% chance of reaching a first interview. The native-German filter, visible Staff promotion and operator credibility help; direct LLM-system and strategic-account experience set the ceiling.
- **Tier 1 fixes:** none remaining that are both evidence-backed and consistent with the user-approved Option A layout.
- **Accepted exception:** the lower quarter-to-third of page 2 remains unused; readability was chosen over padding or lower-value content.
- **Hard ceiling:** about 85/100 from current verified evidence. Direct LLM build/deploy/evaluation, Azure AI delivery, or strategic external-account ownership would be needed to lift it materially.

## Status
- Phase 0: **DONE** (bundle/format/framing confirmed by user 2026-07-27)
- Phase 1: **DONE** (plan confirmed; 12-bullet core + reserves)
- Phase 2 Resume: **DONE** — Summary, Skills, all 5 positions, compiled 2 pages, no overfull boxes

### Phase 2 as-built (differs from the Phase 1 plan — page fill forced it)
Final: **18 bullets / 29 rendered lines** — Swisscom 6×2L, Bosch 5×2L, Fraunhofer 3×1L, Vizrt 2×1L, Generali 2×1L.

The 12-bullet / 20-line plan compiled to a page 2 that was **~40% empty** — far outside the ≤3-line fill gate. All six reserves were added back in the recorded priority order. Net result vs. the Microsoft ISE package (same 18 bullets, 36 lines): **29 lines, ~19% less dense** — the clarity gain came from 1L conversions on the three older positions, not from cutting content.

**Page-fill gate: NOT strictly met.** ~7 lines of white space remain at the bottom of page 2 (gate wants ≤3). Deliberate: the only remaining reserve is SW-6 (PySpark), which is pure filler already covered in Skills. Padding it in would undo the clarity the user asked for. Flagged for the user rather than silently padded.

### Calibration learned (apply to future packages)
`resume_reference.md`'s 1L band of **105–111 chars is too optimistic** for text with many capitals/wide glyphs. At 112 and 115 chars, two 1L bullets wrapped to a second line with single-word orphans ("rescue.", "PoC."). **Empirical safe 1L target for this content class: ~100–105.** Also: LaTeX cannot break slashed compounds (`Teradata/Oracle`, `Athena/Iceberg`) — a pile-up of them caused a 25pt overfull; use "and"/commas instead.

### Accuracy fixes carried into this package
- **RAG removed.** The ISE resume's skills line claimed "custom GPTs with domain grounding (RAG)". SW-8 forbids claiming retrieval implementation — dropped, now reads "domain-grounded agents, custom GPTs".
- **SW-1 scoped** — "Migrated my domains' ETL stack… to Swisscom's cloud-native AWS platform" (not "led migration of the legacy stack").
- **SW-7 scoped** — "governed data products… within Swisscom's company-wide Data Mesh" (not "built a Data Mesh").
- **SW-8 hedged** — "Configured domain-grounded LLM agents… selecting available models and supplying curated domain knowledge bases." No deployment, adoption, RAG or eval claims.
- **SW-5 omitted** entirely (JD silent on security).
- **Generali = Hamburg**; Cologne/Vienna traineeship stations held back for the CL/interview.
- Cover Letter: **EDIT 1 DONE 2026-07-27** — 3 paragraphs, 262 words, 1 page, clean compile, fingerprint scan passed
- Critique: **CURRENT — PASS 2 COMPLETE 2026-07-27, 84.2/100**
- Finalization: **DONE 2026-07-27** — complete artifact check passed; Dennis_Thiessen_Resume.pdf and Dennis_Thiessen_Cover_Letter.pdf created and hash-verified.
- Application: **SUBMITTED 2026-07-27**.
- **Next:** Done — await response.

## KB Issues Found (log to CLAUDE.md KB Corrections)
1. `experience_swisscom.md` SW-5 is titled "Security Champion — 3 Consecutive Years" and its bullets claim 2023/24–2025/26. `config.md` KB Corrections says **2025/2026 only, and it is not an award**. The experience file contradicts config and should be corrected at source.
2. `bundle_data_engineer.md` S3/S5 and SW-1 use unscoped "Led migration of legacy stack" phrasing that violates CLAUDE.md Scope Discipline.
3. `config.md` Role Types references `bundle_semiconductor.md`, which does not exist in `resume_builder/bundles/`.
