feat(aws-fde): Phase 0 for AWS Senior Forward Deployed Engineer, Zurich

Verbatim JD (amazon.jobs 10504263, posted 2026-08-17) retrieved via Playwright
and stored with the session.

Evidence Fit 69/100, Adjacent. All four Basic Qualifications are Direct, so the
minimum-qualification gate passes. Disclosed rather than buried: forward
deployment is the title-defining capability and is a Gap - SW-4, VZ-1 and
global_forbidden_output_patterns all forbid "customer-embedded delivery", and
application_strategy lists strategic-account FDE as a Stretch target. Scored
Adjacent because AWS's published minimum bar is pure software engineering and
the org is seven weeks old, hiring builders at volume.

Assets: AWS is the evidenced cloud (claims.json forbids GCP output), and Kiro -
named in the JD - is in the verified GenAI toolchain.

CL decision YES. Would consume the last Adjacent cohort slot.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

CLAUDE.md

@@ -157,6 +157,7 @@ _Update this section when starting/finishing a JD._
 
 | Session | Status | Next Command |
 |---------|--------|-------------|
+| AWS (AWS EMEA SARL, Switzerland Branch) — Senior Forward Deployed Engineer, AWS Forward Deployed Engineering, Zürich (job 10504263) | **PHASE 0 DONE 2026-08-18** — Adjacent, **Evidence Fit 69/100**, **all 4 Basic Qualifications Direct (minimum-qual gate PASS)**, Channel Weak. Posted 2026-08-17, live. **Disclosed caveat:** forward deployment / customer embedding is the *title-defining* capability and is a **Gap** — `claims.json` SW-4 + VZ-1 + `global_forbidden_output_patterns` all forbid "customer-embedded delivery", and `application_strategy.md` lists strategic-account FDE as a **Stretch** target. Scored Adjacent because AWS's published minimum bar is pure SWE and the org is 7 weeks old ($1bn launch 2026-06-30, hiring builders at volume). Second Gap: R2 multi-agent/retrieval (SW-8 forbids agent orchestration; no RAG/vector evidence). Real asset: **AWS is the evidenced cloud** where GCP is output-forbidden, plus hands-on **Kiro** (named in the JD). Would consume the **last Adjacent cohort slot (2/2)**. CL decision **YES** — the resume alone cannot explain the platform→embedded-delivery move. | Phase 1 — bullet plan (awaiting user confirmation of role type, format, framing) |
 | Google — Forward Deployed Engineer III, Google Cloud GTM (French, German), Zürich (req 78350205438567110) | **CLOSED — NOT PROCEEDING 2026-08-18.** Phase 0 was done (Evidence Fit 67/100, hard gate PASS) but user declined to proceed after **two Google rejections** (Merchant Data Science, Business Home): the bar is now that a Google req must fit *very* well to be worth a third attempt, and this one was Adjacent with an agent-orchestration Gap. **Frees the Adjacent cohort slot (back to 1/2).** Phase 1 never started. | Done — do not reopen without a materially stronger Google req |
 | SDU Center for Energy Informatics, Odense DK — PhD, Theme 2 Predictive Maintenance & Asset Management of Smart Energy Networks (job 4159) | **CLOSED — NOT PROCEEDING 2026-08-18.** Enquiry email to Prof. Bo Nørregaard Jørgensen (sent 2026-08-02) went unanswered for 16 days; user dismissed the idea. Genuine thesis fit (vibration condition monitoring, RBR+ANN hybrid) but the blockers were never the documents — 2 letters of recommendation 13 years out of academia, and DKK 37,075/mo ≈ CHF 56k against a 180k bar. Deadline was 2026-08-20. | Done — no further action |
 | Aker BP ASA — Data Product Architect, AI-ready Data Products (FINN 469067315) | **SUBMITTED 2026-07-30** (ahead of the 2026-08-02 deadline; Adjacent, **Evidence Fit 79/100**, Document Quality 93/100, hard gate PASS, Channel Weak; Stavanger/Oslo/Trondheim, English working language, no Norwegian and no clearance required, EEA work rights). 2pp resume + 1pp CL, both validator PASS. Honest practitioner framing: builds governed data products *inside* Swisscom's Data Mesh; role *authors* an enterprise framework — real level stretch, never fabricate authorship. **Atlassian Compass closed the catalogue-tool gap** (74→79). Remaining gaps: framework authorship, no energy domain, AWS vs their Microsoft/Cognite stack, **zero verified metrics**. | Done — await response; optional follow-up email to Per Olav Marthinsen |

output/AWS_Senior_FDE_Zurich/JD_aws_senior_fde_zurich.txt

@@ -0,0 +1,80 @@
+Skip to main content
+Amazon Jobs home page
+My career
+Senior Forward Deployed Engineer, AWS Forward Deployed Engineering
+
+Job ID: 10504263 | AWS EMEA SARL (Switzerland Branch)
+
+Apply now
+Description
+
+AWS has formed a new Forward Deployed Engineer (FDE) team dedicated to embedding AI Engineers and Scientists directly inside strategic enterprise customer environments to help design, build, and deploy AI-powered production systems. We don’t build from a distance—we sit with customers, work in their infrastructure, and deliver production-grade AI solutions that transform how they operate. This initiative is scaling rapidly.
+
+The Senior Forward Deployed Engineer (FDE) embeds directly inside a strategic enterprise customer to design, build, deploy, and run AI-powered production systems alongside the customer's engineering team. Senior FDEs write production-grade software and own outcomes end-to-end, from prototype through enterprise-scale deployment combining the technical rigor of an AWS SDE with the urgency and ownership required to deliver measurable customer business outcomes. They create reusable architectures, patterns, and engineering mechanisms that scale the entire FDE practice.
+
+Key job responsibilities
+• Embed within customer engineering teams. Understand the customer's business processes, technical architecture, and operational constraints. Translate ambiguous business problems into scalable AI-enabled production systems. Requires up to 30 – 50% travel.
+• Build production AI applications. Design and develop production-grade software powering AI and agentic workflows — orchestration layers for multi-agent systems, retrieval pipelines, workflow automation, decision intelligence. Integrate foundation models, customer data sources, APIs, and existing applications into cohesive AI experiences. Optimize for latency, reliability, observability, cost, and security.
+• Own production. Take systems from design through production rollout and operationalization. Troubleshoot production incidents across AI models, distributed systems, data pipelines, and application services. Put in place monitoring, evaluations, guardrails, and the operational mechanisms (testing, CI/CD, rollback, resiliency) that keep AI systems healthy at scale.
+• Accelerate customer transformation. Identify opportunities to expand AI adoption across customer workflows. Codify reusable patterns, accelerators, and reference architectures that benefit future customers and feed back into AWS.
+• Build and maintain internal AI tools and customer-facing assets and AI-enbled products to accelerate and scale the FDE motion.
+• Route field signal into the closed-loop product feedback mechanism such as filing PFRs, escalating deployment-critical gaps, and feeding delivery learnings that become the next AWS primitives (as we already do with AWS Transform and Kiro).
+• Raise the bar. Mentor engineers. Contribute to AWS engineering best practices for AI and forward deployment.
+
+Basic Qualifications
+
+- - 5+ years of non-internship professional software development experience
+- - 5+ years of programming with at least one software programming language experience
+- - 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
+- - Experience as a mentor, tech lead or leading an engineering team
+
+Preferred Qualifications
+
+- Bachelor's degree in computer science or equivalent
+- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
+- Experience building production AI or ML applications, including agentic workflows
+- Strong written and verbal communication skills; comfort working in customer-facing environments
+
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+
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+
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output/AWS_Senior_FDE_Zurich/session_aws_senior_fde_zurich.md

@@ -0,0 +1,129 @@
+# Session: Amazon Web Services (AWS EMEA SARL, Switzerland Branch) — Senior Forward Deployed Engineer, AWS Forward Deployed Engineering
+
+## JD Integrity
+- File/source: `output/AWS_Senior_FDE_Zurich/JD_aws_senior_fde_zurich.txt` — amazon.jobs job ID **10504263**, `https://www.amazon.jobs/en/jobs/10504263`
+- Retrieval method and date: Playwright headless scrape via `job_scout/.venv`, **2026-08-18**. The `amazon.jobs/*.json` endpoint returns HTTP 406, so the rendered page body was captured.
+- Verbatim posting: **YES** — full visible posting body, not reconstructed.
+- Posting status: **LIVE**, posted **2026-08-17** (one day before retrieval). Legal entity AWS EMEA SARL (Switzerland Branch), Zürich.
+
+## Application Decision
+- Audience profile: **International Tech** (US-tech conventions, role in Europe — config.md default)
+- Evidence Fit: **69/100**
+- Fit class: **Adjacent** (60–74)
+- Hard gate: **PASS on minimum qualifications — but see the title-defining caveat below.** All four Basic Qualifications are Direct. No minimum qualification is a Gap.
+- Channel Strength: **Weak** (cold application; no AWS contact recorded)
+- Channel plan: Cold today. AWS Zurich + a brand-new org announced 2026-06-30 means recruiters are actively sourcing — a targeted note to the FDE recruiter is the highest-value warm action available.
+- Cohort slot: Core 1/7, **Adjacent 1/2 → this would take the last Adjacent slot (2/2)**, Stretch 0/1
+- Decision: **PROCEED — with the gap stated openly, pending user confirmation**
+
+### The caveat that must not be buried
+`critique_framework.md` triggers a NO-GO flag when "a title-defining capability is not Direct."
+**Forward deployment — embedding inside a strategic enterprise customer — is exactly that, and it is a Gap.**
+The evidence base actively forbids the claim:
+
+- `claims.json` **SW-4 forbidden:** `"customer-embedded delivery"`, `"strategic customer delivery"`, `"C-suite advisor"`
+- `claims.json` **VZ-1 forbidden:** `"customer-embedded"`
+- `claims.json` **global_forbidden_output_patterns:** `"customer-embedded delivery"`
+- `application_strategy.md` lists **"strategic-account FDE" under Stretch targets**
+- `historical_outputs.json` marks `output/Microsoft_ISE_Senior_SWE` unsafe for exactly this: *"customer-delivery framing exceeds verified evidence"*
+
+So the single phrase that best describes this job is one we are never allowed to write about Dennis.
+This is scored as Adjacent rather than No-Go because AWS's *published minimum bar is pure software
+engineering* (see Requirements table) — they are hiring builders into a new org and transferring the
+embedded model, not requiring prior consulting tenure. That is a real argument, not a rationalisation,
+but it is an argument about AWS's intent, not about Dennis's evidence.
+
+## Requirements
+
+| # | Requirement | Required/preferred | Direct/Adjacent/Gap/Constraint | Canonical evidence | Gate? |
+|---|---|---|---|---|---|
+| B1 | 5+ years non-internship professional software development | Required | **Direct** | Continuous employment 2014-11 → present (~11.5 yrs) | Yes — PASS |
+| B2 | 5+ years programming with at least one language | Required | **Direct** | Python, Java, C#, C++ across SWISSCOM/BOSCH/FRAUNHOFER/VIZRT (BS-2, VZ-1, FC-3) | Yes — PASS |
+| B3 | 5+ years leading design or architecture (design patterns, reliability, scaling) of new **and existing** systems | Required | **Direct** | SW-2 Component Owner of business-critical Fulfillment ETL (operation, data quality, incidents, on-call); BS-3 Application Owner with SLOs; SW-3 Python apps on Kubernetes + GitLab CI/CD; SW-7 governed data products | Yes — PASS |
+| B4 | Experience as a mentor, tech lead, or leading an engineering team | Required | **Adjacent** | Staff Engineer IV (Apr 2025→); BS-3 training and documentation; GN-1 trained teams on BDD/test automation; Leadership Cohort 2025. **No formal tech-lead title or direct reports.** | Yes — PASS (hedged) |
+| P1 | Bachelor's in CS or equivalent | Preferred | **Direct** | M.Eng. Computer Aided Engineering (Software Design & Engineering), UniBw München | No |
+| P2 | 5+ years full SDLC — coding standards, code review, source control, build, testing, operations | Preferred | **Direct** | VZ-2 automated A/V integration tests wired to CI/CD; FC-1 Jenkins CI/CD; SW-3 GitLab CI/CD; GN-1 test automation | No |
+| P3 | Experience building production AI or ML applications, **including agentic workflows** | Preferred | **Gap (agentic) / Adjacent (production ML)** | BS-1 integrated containerized ML inference into 24/7 semiconductor production — genuine production ML. **But SW-8 forbids `"agent orchestration"`, `"built production LLM systems"`.** No RAG, no vector DB, no multi-agent framework anywhere in claims.json | No |
+| P4 | Strong written/verbal communication; comfort in customer-facing environments | Preferred | **Adjacent** | SW-4 delivers data products with **internal B2B** stakeholders and product owners — explicitly *"not external consulting or strategic-account delivery"* | No |
+| R1 | Embed within customer engineering teams; **up to 30–50% travel** | Responsibility (title-defining) | **Gap + Constraint** | No evidence; forbidden phrasing (SW-4, VZ-1, global). Travel itself is workable — user is travel-OK from a Bern base, no relocation | — |
+| R2 | Build production AI apps: orchestration layers for multi-agent systems, retrieval pipelines, workflow automation | Responsibility | **Gap** | SW-8 forbids agent orchestration. Real adjacent: configured domain-grounded LLM assistants, LiteLLM gateway, custom GPTs, Copilot, **Kiro** | — |
+| R3 | Own production — rollout, incidents across models/distributed systems/data pipelines, monitoring, CI/CD, rollback, resiliency | Responsibility | **Direct** | SW-2 (incidents, on-call, data quality), SW-3 (K8s + CI/CD), BS-3 (SLOs), BS-4 (ELK/Kafka anomaly detection + monitoring) | — |
+| R4 | Codify reusable patterns, accelerators, reference architectures | Responsibility | **Adjacent** | SW-7 data-product modelling and documentation; BS-5 Spotfire C# extensions co-owned | — |
+| R5 | Build internal AI tools to scale the FDE motion | Responsibility | **Adjacent** | SW-8 LiteLLM APIs, custom GPTs with fed domain knowledge | — |
+| R6 | Route field signal into product feedback (PFRs) | Responsibility | **Adjacent** | SW-4 stakeholder translation; BS-3 vendor management | — |
+| C1 | Location Zürich; work authorization | Constraint | **Direct** | German citizen (EU) + Swiss B permit — no sponsorship. Bern→Zürich ~1h by rail | — |
+| C2 | English working language | Constraint | **Direct** | English fluent; German native (bonus for DACH accounts) | — |
+
+**Tally:** Required 3 Direct + 1 Adjacent, **0 Gap** → minimum-qualification gate PASSES.
+Responsibilities: 1 Direct, 3 Adjacent, **2 Gap** — one of which is title-defining.
+
+## Evidence Fit — dimension table
+
+| Dimension | Weight | Score | Reasoning |
+|---|---:|---:|---|
+| Required qualifications | 35 | **29** | All four Basic Quals Direct/near-Direct; B4 hedged (no formal lead title). Preferred P3 agentic is a Gap. |
+| Core responsibilities | 25 | **11** | Only R3 (own production) is Direct. R1 embedding and R2 agentic are Gaps; R1 is title-defining. |
+| Level and ownership | 15 | **9** | Staff Engineer IV + Component/Application Owner matches "Senior" IC scope well. No external-account authority. |
+| Recency and depth | 10 | **8** | Current, substantial: AWS, Kubernetes, Python, production ownership all present-tense at Swisscom. |
+| Domain/tool transfer | 10 | **7** | **AWS is the ecosystem match** (contrast: claims.json marks GCP `output: forbidden`). Bedrock/AgentCore unused but adjacent to LiteLLM. Kiro genuinely used. |
+| Practical constraints | 5 | **5** | Zürich commutable, EU citizen + B permit, English, travel acceptable. |
+| **Total** | **100** | **69** | **Adjacent** |
+
+## Competitive Read
+- **Obvious-fit candidate:** a consulting-side senior engineer from AWS ProServe, Palantir, Accenture Applied Intelligence or a Big-4 AI practice who has already shipped LLM/agentic systems *inside* client environments, and who is used to 50% travel and client politics.
+- **Dennis's advantage:** genuine **production ownership** — on-call, incidents, SLOs, data quality on business-critical pipelines. Many FDE applicants are strong at prototypes and weak at running things. He also brings AWS-native depth, native German for DACH accounts, and hands-on Kiro use (AWS's own agentic IDE, named in the JD).
+- **Their advantage:** they have actually done the title-defining thing — embedded delivery against strategic accounts — and they have the agentic/RAG production track record listed in the preferred quals.
+- **Level/scope comparison:** Level matches (Senior IC, not people-management). The gap is *function*, not seniority. That is the honest read.
+
+## Company Context
+- **The org is 7 weeks old.** AWS announced Forward Deployed Engineering on **2026-06-30** with a **$1bn** commitment, planning to deploy *thousands* of engineers. Model: small teams of ~5–6 embedded at customer sites for ~45-day engagements. Explicitly positioned as **not traditional consulting** — the stated goal is transferring expertise so customers operate the systems themselves. The JD's "This initiative is scaling rapidly" is literal.
+- **Why that matters for Dennis:** a brand-new org hiring at volume screens differently from a mature consulting practice. They need builders who can run production, and they are training the embedded motion. This is the strongest structural argument for an Adjacent application.
+- **Kiro** — the JD says "as we already do with AWS Transform and Kiro." Kiro is AWS's spec-driven agentic IDE, GA March 2026, successor to Amazon Q Developer, routing Claude Sonnet + Amazon Nova over Bedrock. **Dennis uses Kiro** (config.md verified GenAI toolchain). This is a rare, first-party, verifiable hook — not a vocabulary match.
+- **AWS Zurich** office is operational with active hiring (Delivery Consultant, Practice Manager, Solutions Manager roles alongside this one).
+
+## Framing Strategy
+- **Professional identity:** Staff-level engineer who **builds and runs production systems on AWS** — pipelines, data products, containerized services — and has integrated ML inference into a 24/7 industrial environment.
+- **Lead narrative:** *"I don't hand over prototypes; I own what happens at 3am."* Production ownership is the honest differentiator against a prototype-heavy FDE applicant pool.
+- **Strongest proof points:** SW-2 Component Owner (incidents/on-call/data quality) · BS-1 containerized ML inference into 24/7 semiconductor production · SW-3 Python on Kubernetes + GitLab CI/CD · SW-7 governed data products on AWS · BS-4 ELK/Kafka anomaly detection.
+- **Honest adjacent bridges:**
+  - AI work → frame as **integration and enablement** (configured domain-grounded assistants, LiteLLM gateway, Kiro, Copilot), never as agent orchestration.
+  - Customer-facing → frame as **internal B2B stakeholder delivery and vendor/Application ownership** (SW-4, BS-3), never as embedded or strategic-account delivery.
+- **Explicit gaps — do not paper over:** no customer-embedded delivery; no multi-agent/RAG production systems; no Bedrock/AgentCore.
+- **Downplay:** Security Champion (JD has no security requirement — CLAUDE.md default is OMIT); semiconductor domain depth beyond the ML-inference story.
+- **User directives:** none given for this JD.
+
+## Critique Context
+- **Reviewer persona:** an AWS FDE hiring manager staffing a brand-new org at speed — pragmatic, bar-raiser-trained, scanning for "can this person build *and* operate under customer pressure."
+- **Amazon-specific:** Leadership Principles matter. *Ownership*, *Bias for Action*, *Dive Deep*, *Deliver Results* are the ones his evidence genuinely supports. Amazon interviews are LP-heavy — worth noting for interview prep, not for resume prose.
+- **Domain vocabulary:** forward deployed, production-grade, end-to-end ownership, foundation models, Bedrock, agentic workflows, evaluations, guardrails, observability, latency/cost optimization, reference architectures, PFR.
+- **Likely first technical challenge:** *"Walk me through an AI system you took to production."* The honest answer is BS-1 (containerized ML inference, 24/7 fab) — classical ML, not LLM. Prepare that answer deliberately; do not let it drift toward implying LLM production ownership.
+
+## Cover Letter Decision
+- **YES**
+- **Reason:** The resume cannot, on its own, explain why a Swisscom platform engineer is applying to an embedded customer-delivery role. That gap is visible on page one and will otherwise be resolved against him. A letter is the only place to address it directly and turn production ownership into the argument.
+- **Information it adds beyond resume:** (1) the motivation for moving from internal platform work into forward-deployed delivery, stated plainly rather than disguised; (2) **hands-on Kiro use** — first-party AWS tooling named in the JD; (3) native German for DACH accounts; (4) travel/mobility willingness from a stable Swiss base.
+- **Verified hook sources:** JD text (Kiro, AWS Transform, PFR mechanism); AWS FDE launch 2026-06-30 ($1bn, ~45-day embedded engagements); config.md verified GenAI toolchain (Kiro, Copilot, LiteLLM, custom GPTs).
+- **Forbidden in the letter:** any phrasing implying prior customer-embedded or strategic-account delivery; any agent-orchestration claim.
+
+## Resume Plan
+- Summary: 2–3 lines — production ownership + AWS + ML-into-production
+- Skills: 4–6 evidence-backed lines; AWS prominent; **no Bedrock, no LangGraph/CrewAI/ADK, no vector DB**
+- Swisscom: SW-2, SW-3, SW-7, SW-1, SW-8 (integration framing only)
+- Bosch: BS-1 (lead), BS-3, BS-4
+- Earlier experience: VZ-1 or VZ-2 (distributed systems / CI/CD), FC-3 optional
+- Total bullets: 11–14
+- Impact evidence still needed: **all Swisscom metrics are `unverified`** — this remains the standing weakness across every package.
+
+## Output Files
+- JD (verbatim): `output/AWS_Senior_FDE_Zurich/JD_aws_senior_fde_zurich.txt`
+- Resume: pending Phase 2
+- Cover letter: pending (decision YES)
+- Critique: pending
+
+## Status
+- Fit gate: **Phase 0 DONE 2026-08-18** — Adjacent, Evidence Fit 69/100, minimum-qual gate PASS, title-defining Gap disclosed, Channel Weak
+- Phase 0: DONE
+- Phase 1: PENDING — awaiting user confirmation of (1) role type + bundle, (2) format, (3) framing strategy
+- Resume: PENDING
+- Cover Letter: PENDING (decision YES)
+- Critique: PENDING