# Session: Google — Forward Deployed Engineer III, Google Cloud GTM (French, German), Zürich

## JD Integrity
- **File/source:** `output/Google_FDE3_Cloud_GTM/JD_google_fde3_cloud_gtm.txt` — copied verbatim from `job_scout/jd_google_fde3_gtm.txt`
- **Source URL:** https://www.google.com/about/careers/applications/jobs/results/78350205438567110-forward-deployed-engineer-iii-google-cloud-gtm-french-german?location=Switzerland
- **Retrieval method and date:** job_scout Playwright headless Chromium (`inner_text('body')`), 2026-08-11. NOT WebFetch (JS-blind on Google Careers).
- **Verbatim posting:** YES — full min/preferred quals, About the job, and Responsibilities captured
- **Posting status:** LIVE 2026-08-11 — present in the Google Zürich board listing (32 rows). Sibling req *FDE III, Generative AI (French, German)* returned "Job not found" on the same scrape and is logged closed.
- **Level badge on posting:** `Mid`

## Application Decision
- **Audience profile:** International Tech (default; US-tech conventions, Zürich office)
- **Evidence Fit:** **67/100**
- **Fit class:** **Adjacent** (60–74)
- **Hard gate:** **PASS** — no minimum qualification is a Gap. See caveat below.
- **Channel Strength:** **Weak** (cold application; no referral, no recruiter contact)
- **Channel plan:** Cold at submission. Warm action outstanding — see Channel Action.
- **Cohort slot:** Adjacent **2/2** (cohort `evidence-first-2026-01`, currently core 1/7, adjacent 1/2, stretch 0/1). **This consumes the last Adjacent slot.**
- **Decision:** **PROCEED** — user override recorded below.

### Level override (explicit, do not re-litigate)
User instruction 2026-08-11, verbatim: *"ignore fit, i would gladly accept a mid FAANG offer."* This is the **second** explicit override (first recorded 2026-06-20 in `user_comp_bar`). Level, seniority and the CHF 180k bar are **NOT** to be scored as gaps or raised as objections for FAANG reqs. Screen these reqs on hard capability gates only.

### Hard-gate caveat (must be stated, not buried)
The gate passes on the letter of the minimum qualifications. It is weaker on the **title-defining capability**: `critique_framework.md` §1 flags NO-GO when a title-defining capability is not Direct. Responsibility #1 — *"lead developer … production-grade agentic workflows (multi-agent systems, MCP servers)"* — is a **Gap**, not a Bridge, because SW-8 explicitly forbids claiming agent orchestration or production LLM systems. Classed Adjacent rather than No-Go because that capability appears in **Responsibilities and Preferred quals, never in Minimum quals**. This is the single serious gap permitted under the Adjacent rule — there must not be a second.

## Requirements

### Minimum qualifications (all five must hold — none is a Gap)
| # | Requirement | Req/Pref | Class | Canonical evidence | Gate? |
|---|---|---|---|---|---|
| 1 | Bachelor's degree or equivalent practical experience | Required | **Direct** | EDU-BENG (B.Eng.), EDU-MENG (M.Eng.) | YES — pass |
| 2 | 2 yrs software development in one or more programming languages | Required | **Direct** | ~13 yrs; Python/SQL production-current, Java/C# production-historical. **No language specified — no C++ gate on this req.** | YES — pass |
| 3 | 1 yr ML infrastructure (model deployment, evaluation, optimization, **data processing, debugging**) | Required | **Bridge (high)** | BS-1 containerized ML inference deployed into 24/7 fab production = genuine model-deployment infrastructure; SW-1/SW-3/SW-6 data processing on Kubernetes | YES — pass on deployment + data processing. **Do NOT claim model evaluation** (forbidden). |
| 4 | GenAI techniques (LLMs, multi-modal, LVMs) **or** GenAI-related concepts (language modeling, computer vision) | Required | **Bridge (medium)** | SW-8 domain-grounded LLM assistants, LiteLLM, custom GPTs, Kiro, Copilot. **Computer-vision branch:** BS-1 image-classification inference, BS-2 wafer inspection images. | YES — pass via the "or concepts" branch |
| 5 | Ability to communicate in **French or German** fluently | Required | **Direct** | German native. Disjunctive — French not required. | YES — pass |

### Preferred qualifications
| # | Requirement | Class | Canonical evidence / note |
|---|---|---|---|
| 6 | Master's or PhD in AI, CS or related technical field | **Direct** | EDU-MENG, M.Eng. Computer Aided Engineering (display focus: Software Design & Engineering) |
| 7 | Multi-agent systems via LangGraph / CrewAI / Google ADK; ReAct, self-reflection, hierarchical delegation | **GAP — hard** | LangGraph/LangChain/LlamaIndex are `forbidden: never-used`. SW-8 forbids "agent orchestration". **Never fabricate. This is the serious gap.** |
| 8 | LLM-native metrics (tokens/sec, cost-per-request), state management, granular tracing | **Weak bridge** | LiteLLM gateway gives honest token/cost-routing exposure; BS-4 ELK/Kafka monitoring is real observability. Do not inflate into LLM-native observability ownership. |
| 9 | Secure agentic workflows: MCP, tool-calling, OAuth-based auth | **Gap** | No MCP evidence. Adjacent only: API/security-perimeter integration work. |

### Responsibilities
| # | Responsibility | Class | Canonical evidence |
|---|---|---|---|
| R1 | Lead developer, prototypes → production agentic workflows (multi-agent, MCP servers) driving ROI | **Gap** | SW-8 forbidden territory. Title-defining — see caveat above. |
| R2 | Architect/code the "connective tissue" between Google AI products and customer live infra — APIs, **legacy data silos**, security perimeters | **Direct** | SW-1 legacy Teradata/Oracle ETL migration (own domains), SW-7 source onboarding into governed data products, BS-2 Oracle/Hadoop services. **Strongest single match in the JD.** |
| R3 | Build evaluation pipelines and observability frameworks for accuracy, safety, latency | **Bridge (medium)** | BS-4 ELK/Kafka anomaly detection + monitoring; SW-2 data quality/incidents/on-call. **"formal model evaluation" is globally forbidden — frame as data/pipeline quality + observability, never model eval.** |
| R4 | Identify repeatable field patterns → reusable modules / product feature requests | **Bridge** | SW-7 governed data products as reusable assets; BS-5 Spotfire C# extensions |
| R5 | Co-build with customer engineering teams; instill best practices, drive adoption | **Bridge (medium)** | SW-4 internal B2B stakeholders/product owners; BS-3 Application Owner (training, vendors, SLOs, docs); BS-5 co-presented TIBCO Analytics Forum 2022. **SW-4 forbids "customer-embedded delivery"/"strategic customer delivery" — internal-stakeholder scope must stay visible.** |

### Constraints
| Constraint | Status |
|---|---|
| Zürich, Switzerland — hybrid | **Workable** — commutable from Bern; within stated Bern/Basel/Zürich radius |
| Work authorization | **Direct** — German citizen (EU), Swiss B permit, no sponsorship needed |
| Google Cloud / Vertex AI / Gemini Enterprise ecosystem | **GAP** — GCP is `forbidden: unverified` in claims.json. AWS-primary. Not a minimum qual, but it is the employer's own stack. State honestly; never imply GCP production experience. |
| Google application quota | 1 of 3 rolling-30-day slots used (Business Home, 2026-07-27). Slot available. |

## Evidence Fit — dimension table
| Dimension | Weight | Score | Reasoning |
|---|---:|---:|---|
| Required qualifications | 35 | 26 | All 5 minimums hold; 2 Direct, 3 Bridge. None is a Gap. |
| Core responsibilities | 25 | 13 | R2 Direct and strong; R3–R5 Bridge; **R1 (the defining one) is a Gap**. |
| Level and ownership | 15 | 12 | Staff scope against a Mid req — over-clears. Deduction is for external-customer delivery ownership (internal-only), not for level. |
| Recency and depth | 10 | 6 | Swisscom data/AI-foundation work is current and substantial; GenAI exposure is configuration-level, not delivery-level. |
| Domain/tool transfer | 10 | 5 | AWS→GCP is genuinely transferable; agent frameworks (ADK/LangGraph) are **not** substitutable by anything he has. |
| Practical constraints | 5 | 5 | Native German, EU citizen + B permit, Zürich commutable. |
| **Total** | **100** | **67** | **Adjacent** |

## Company Context
- **Google Cloud is scaling FDE hiring hard in 2026** — reporting describes ~59 FDE reqs across US/London/Paris/Hong Kong and "hundreds" of hires, an embedded role shipping production AI inside customer organisations. A funded build-out hiring at volume is materially better odds than a single backfill req — the same structural argument that made the Microsoft Frontier req attractive.
- **$750M partner fund (2026-04-22)** explicitly funds "teams of embedded Google forward-deployed engineers" across the 120,000-member partner ecosystem, covering AI value identification, agentic prototyping, agent building/deployment and upskilling. This is the budget line this role sits on.
- **Cloud Next 2026 renamed Vertex AI to the Gemini Enterprise Agent Platform**, absorbing Agentspace. **Note the JD still says "the complete Vertex AI platform"** — the posting predates or ignores the rename. Use the JD's own vocabulary in the documents; knowing the rename is useful for an interview, not for the resume.
- **ADK v1.0** shipped stable across four languages with a graph-based multi-agent framework; **every Google Cloud service is now MCP-enabled by default**, with managed MCP servers via Apigee. A2A protocol v1.0 in production at ~150 organisations.
- **DACH:** Google Cloud runs a DACH developer summit and is pushing agentic-workplace transformation with DACH enterprises. German-language delivery from Zürich is a real, funded lane.
- **"Why them" angle:** Google's own framing is that the hard part is production reality inside the customer's environment — APIs, legacy data silos, security perimeters. That is precisely Dennis's decade: he has been the person *inside* the large regulated European enterprise whose messy data the agents must query.

## Competitive Read
- **Obvious-fit candidate:** A GCP-certified consultant from a Google partner (Accenture/Devoteam/Onix) with Vertex AI / ADK delivery scars and German, or an ex-Palantir/ex-Google FDE. Alternatively a strong Mid-level Google-internal transfer.
- **Their advantage:** Direct GCP/Vertex/ADK production work, real multi-agent shipping, customer-facing delivery titles, and often an internal referral.
- **Dennis's advantage:** He has *been the customer*. Ten-plus years inside large regulated European enterprises (Swisscom telco, Bosch semiconductor fab) shipping into unforgiving production; genuine legacy-data-silo and security-perimeter integration; native German; and the governed-data-foundation layer that agentic pilots keep dying on. Consultants usually leave before the pager.
- **Level/scope comparison:** He is *over*-levelled for a Mid req, which is a screening risk (see below), not an evidence weakness.

## Framing Strategy
- **Professional identity:** A production engineer from inside large regulated European enterprises who builds the governed data foundation and integration layer that enterprise AI runs on — now bringing that to Google Cloud's customers, in German.
- **Lead narrative:** Play the **insider-operator** card, not the consultant card, and not the AI-researcher card.
- **Strongest proof points:**
  - R2 anchor — legacy data silos, API integration, security perimeters (SW-1, SW-7, BS-2)
  - BS-1 — containerized ML inference shipped into a 24/7 fab with no deployment window (covers min qual 3 *and* the "production-grade reality" theme)
  - SW-7 — governed data products + Atlassian Compass metadata/lineage = the grounding layer agents query
  - Native German + Swiss/DACH enterprise fluency (min qual 5, and the reason this req narrows)
  - BS-3 / BS-5 / TAF 2022 — enablement, training and technical evangelism to stakeholders
- **Honest adjacent bridges:**
  - Internal B2B stakeholder delivery → co-building with customer engineering teams (**keep internal scope visible**)
  - LiteLLM / custom GPTs / Kiro / Copilot → GenAI integration at configuration level (min qual 4)
  - BS-4 ELK/Kafka observability → evaluation/observability frameworks (**pipeline and data quality, never model evaluation**)
- **Explicit gaps — state or omit, never fabricate:**
  - Multi-agent frameworks (ADK, LangGraph, CrewAI), ReAct/hierarchical delegation — **omit entirely; forbidden**
  - MCP, tool-calling, OAuth agentic auth — **omit**
  - GCP / Vertex AI / Gemini Enterprise production experience — **omit from resume; AWS stated honestly**
  - LLM fine-tuning, formal model evaluation — **globally forbidden**
- **User directives:** Level/comp is not a gap (override). Enforce Scope Discipline on Swisscom Data Mesh (SW-7 forbidden verbs). Never substitute LangChain/LangGraph for the real toolchain.

## Critique Context
- **Reviewer persona:** A Google Cloud AI GTM hiring manager or FDE peer in Zürich, screening a high-volume req. Impressed by: evidence of carrying something into a hostile production environment and owning the pager; concrete integration against legacy systems; German. Bored by: tool soup, "passionate about AI", advisory language with no shipping evidence, and any whiff of overclaimed agent work they will puncture in ten seconds.
- **Likely first technical challenge:** *"Walk me through an agentic system you put into production."* There is no honest answer that says "I did." The honest answer pivots to the grounding/data/integration layer and to BS-1 as production ML delivery. **Prepare this before any call — it is the screening risk, the same shape as the BIS LLM-depth probe.**
- **Domain vocabulary:** "time to value", "production-grade", "grounding", "data readiness", "connective tissue", "eval pipelines", "field patterns". Outsider tells: calling FDE work "consulting", "solutioning", implying pre-sales.

## Cover Letter Decision
- **YES** — required, and for a specific job beyond skills coverage.
- **Reason:** Two things the resume structurally cannot do. (1) **Pre-empt the overqualification screen.** Google Business Home (Mid req, Staff-scope resume) was submitted 2026-07-27 and dispositioned "Not proceeding" on 2026-07-28 — roughly 24 hours, too fast to be a content read. The letter must say plainly why a Staff-scope engineer wants this seat and that level is secondary. (2) **Own the German + DACH-enterprise angle** as motivation rather than as a keyword.
- **Information it adds beyond resume:** deliberate level intent; why Google Cloud specifically (the embedded-FDE build-out and the data-readiness thesis); German-language delivery to DACH enterprises from Bern.
- **What it must NOT do:** apologise, sandbag the evidence, or imply agentic/GCP experience. Fabricating *downward* violates the same accuracy rule as fabricating upward.
- **Verified hook sources:** Google Cloud $750M partner fund (2026-04-22, Google Cloud Press Corner); FDE scale-up reporting (Metaintro/CIO Dive); Cloud Next 2026 Gemini Enterprise Agent Platform rename + ADK v1.0 + managed MCP servers (Google Cloud Blog, Google Developers Blog).

## Channel Action (REQUIRED — do not skip)
Cohort data is unambiguous: **0 strong, 0 moderate, 2 weak channels; 7 cold applications rejected at screen with no interview.** Tailoring has never been the failing variable. Before or immediately after submitting, attempt one warm action — Swisscom network into Google Zürich, or a targeted note to the AI GTM recruiter. Record the result and upgrade Channel Strength if it lands.

## Resume Plan (draft — confirm in Phase 1)
- **Summary:** 2–3 lines — insider-operator identity, German, production integration
- **Skills:** 4–6 evidence-backed lines; AWS stated honestly; **no GCP, no agent frameworks**
- **Swisscom:** ~4–5 bullets (SW-7, SW-1, SW-3, SW-4, SW-8 hedged)
- **Bosch:** ~3–4 bullets (BS-1 lead, BS-2, BS-3, BS-5)
- **Earlier experience:** 0–1 per role (Fraunhofer FC-3, Vizrt VZ-1/VZ-2, Generali GN-1)
- **Total bullets:** 11–14, natural length, no page-fill quota
- **Impact evidence still needed:** all canonical metrics are `unverified` — no invented numbers anywhere

## Output Files
- Resume: `output/Google_FDE3_Cloud_GTM/e2e_google_fde3_cloud_gtm_resume.tex` (pending)
- Cover letter: `output/Google_FDE3_Cloud_GTM/e2e_google_fde3_cloud_gtm_cover_letter.tex` (pending — decision YES)
- Critique: `output/Google_FDE3_Cloud_GTM/critique_google_fde3_cloud_gtm.md` (pending)

## Status
- **Fit gate:** DONE — Adjacent 67/100, hard gate PASS with stated caveat, PROCEED
- **Phase 0:** DONE
- **Phase 1:** PENDING
- **Resume:** PENDING
- **Cover letter:** PENDING (decision YES)
- **Critique:** PENDING
- **Application/outcome:** not submitted
- **Next:** Phase 1 — bullet plan
