# Blind hiring review — paste-able prompt for an external model This file holds a self-contained prompt for running the same blind CV/role-match exercise against a different model (Gemini, ChatGPT, or any chat AI with web-fetching). Paste everything below the `--- COPY BELOW ---` line into a fresh chat session in your target model. Purpose: mirror the local blind review with a different model's lens, then compare the two outputs. The inside-editor review step is intentionally *not* included — that's the local-roster follow-up after the cold read, and reproducing it externally would defeat the comparison. **Tips for the target chat:** - Use a fresh chat (no prior conversation context about Stefan or this project). - If your model supports it, enable browsing / URL context so the model can actually fetch the website and the linked public repositories. Gemini: "Deep Research" or the URL-context tool. ChatGPT: web search on. Claude.ai: the web search tool. - If your model can't browse, the exercise won't work — the site and the repositories it links to are the load-bearing input. --- COPY BELOW --- You are a senior engineering hiring manager doing a blind, first-pass review of a candidate. You have access to **two input sources and two only**: 1. The candidate's public personal site at **https://about-me.wagen.io**, **plus the public source repositories that site links to**. Please fetch the site now and explore the sub-pages — `/professional`, `/tennis`, `/personal`, `/projects`, and the German-language versions at `/de/*` (e.g., `/de/professional`, etc.). On `/projects`, several project cards carry a `repo →` link to a public source repository hosted under `gitlab.com/wagen-public/*` (the AI-build cluster's published snapshots). **Follow those `repo →` links and read the linked repositories** — they are in scope precisely because the site offers them as evidence. Use **only** the site and the repositories it links to. Do not search for the candidate's name anywhere else; do not look up the person on LinkedIn or any other site; do not browse to repositories the site does not link to. If the candidate appears in your training data, ignore that — operate only from the site and its linked repositories. 2. The eight role profiles included below under "Role profiles to match against." Do not invent context. Do not hedge. If a piece of evidence isn't visible on the site, in the linked repositories, or in the role profiles, treat it as absent — "no evidence of X on the site" is a valid, useful finding. Open your output with this exact line, then proceed: > Blind external review — inputs: https://about-me.wagen.io (and the public repositories it links to) and the eight role profiles supplied in this prompt. This makes any source-bleed (e.g., training-data leakage about the candidate) visible. ## What to deliver ### Part 1 — Candidate brief A short, dense brief of the candidate, split: - **Person** — 2–4 bullets covering trajectory, register, stance, and ambition signal as visible on the site. - **Professional** — 4–6 bullets covering scope, evidence, signature work, and visible gaps. Each bullet self-carrying, anchored to a specific page, section, or linked repository (e.g., "(from /professional, who-i-am lede)", "(from /projects, AI-build cluster)", or "(from the linked ai-learning-journey public repo)"). ### Part 2 — Match table For each of the eight role profiles, in this shape: ``` ## Role N — **Band:** Strong fit / Plausible fit / Stretch / No fit **Rationale:** 3–6 sentences. Anchor every claim to (a) language from the role profile and (b) evidence on the site or in a linked repository. No hedge prose. **What's missing / unclear:** one or two sentences naming what the role profile asks for that the public material doesn't show. ``` Reuse the candidate brief across all eight roles. Don't rewrite the candidate per role. ### Part 3 — Hiring-manager verdict One paragraph. Which of the eight roles would you prioritise for an initial interview, and why? Which is the clearest no-fit, and why? Where on the public-facing material is the candidate carrying the strongest signal, and where the weakest? ## Hard rules - Inputs are the site, the public repositories it links to, and the eight role profiles below. Nothing else. - Bands not bare numbers. Use the four-band scale: Strong fit / Plausible fit / Stretch / No fit. - Rationale is the deliverable; the band is the index into it. - Don't soften findings to be polite. Don't inflate findings to flatter. Hiring-manager language, not PR-safe language. - Don't fabricate qualifications. If you'd need to invent a credential to make a match work, mark it as a stretch instead. ## Role profiles to match against # Candidate job profiles for Stefan — public-facing match-score input **Purpose:** Feed alongside https://about-me.wagen.io (and the public repositories it links to) into a downstream HR/hiring agent that will (a) summarise public-facing Stefan and (b) produce a match score per posting. Two questions in play: how the site reads cold to a hiring manager who has never met Stefan, and which next-rung targets the public-facing material currently fits best vs. surfaces as gaps. **Scoping logic.** Eight profiles. Distribution chosen to triangulate the real next-rung landscape, not to fantasise. - **Levels.** Three Senior-IC / Staff+ shapes with AI-build as a real lever (#2, #5, #8). Three EM / engineering leadership shapes at peer-to-stretch scope (#1, #3, #4). Two stretch / Director-leaning shapes (#6, #7) to surface aspirational gaps. - **Industries.** Five financial-services-anchored (#1, #2, #3, #6, #8), two big-tech-secondary (#4, #5), one infra/platform engineering outside finance to test transferability (#7). - **Company shapes.** Tier-1 universal bank (#1, #6), wealth-tech scale-up (#3), established Swiss private bank (#8), big-tech engineering centre (#4, #5), fintech scale-up (#2), cloud-native infra company (#7). - **Geography.** Six CH / Zürich-anchored or commutable-from-Horgen (per Stefan's hard constraint), one remote-friendly EU (#5), one Singapore-shaped (#3) to honour the Singapore-on-the-table locked decision. Real company names are not used. Where an archetype helps a hiring agent calibrate, the shape is described — at most referencing prior employers Stefan has worked at (UBS-shape, CS-shape pre-2023) as comparators. Compensation indications are anchored to CH market bands (Stefan's current TC ≈ CHF 190k; any next-rung must clear it meaningfully). --- ## 1. Engineering Manager, Wealth Management Platforms — Tier-1 Swiss Universal Bank **Location:** Zürich, on-site / hybrid (3 days office) **Level:** Engineering Manager (Director-equivalent internal grade) **Reporting to:** Head of Wealth Management Engineering ### About the role Lead a chapter of 12–18 engineers and business analysts delivering on a strategic wealth-management platform serving discretionary mandates and advisory mandates across multiple booking centres. The chapter sits inside a Spotify-style crew structure and owns end-to-end delivery, from solution design through production operation, for two core applications and their cross-system integrations. ### Responsibilities - Line-manage a mixed chapter of internal engineers, BAs, and a stable contractor cohort; own performance management, hiring, capability development. - Partner with product owners and a stream-level architect on the multi-quarter roadmap; accountable for delivery, not just coordination. - Drive a modernisation track on legacy components (Java/Spring + Oracle → Spring Boot + Postgres + cloud) running in parallel with feature delivery. - Operate AI-assisted engineering practice across the chapter — adoption of internal Copilot-equivalent tooling, evolve role definitions for BA + QA functions facing automation. - Represent the chapter in cross-crew architecture and risk forums; surface and escalate cross-application data-flow and interface issues early. ### Must-have - 8+ years engineering experience, of which 4+ in people-management roles at chapter / team-lead / EM scope (10+ direct reports at some point). - Hands-on background in Java/Spring backends and one modern front-end stack; able to read code in review and shape architecture discussions credibly. - Track record delivering complex programmes in regulated financial services (wealth management, asset management, banking). - Demonstrable experience operating a hybrid internal + contractor team, including ramp-up / ramp-down dynamics. - Comfortable in a Spotify-style organisation (crews, chapters, pods, stream-level architecture). - German and English at working-business level. ### Nice-to-have - First-hand experience with AI-assisted development workflows (Copilot, Claude, agentic tools) and a point of view on what it changes for BA + QA functions. - Prior single-point-of-contact role on a cross-border migration or integration programme (UBS/CS-shape integration, similar). - Experience with Eclipse RCP or other rich-client legacy modernisation. ### Compensation indication CHF 220–260k base + 25–40% variable. Pension and benefits per CH banking norm. --- ## 2. Staff Engineer, Agentic AI Platforms — Zürich Fintech Scale-up **Location:** Zürich (hybrid, 2 days office) **Level:** Staff / Principal Engineer (IC) **Reporting to:** VP Engineering ### About the role Senior-IC role anchoring the agentic-AI build practice inside a Series-C fintech (≈ 200 engineers) that is shipping AI-driven products into regulated wealth and credit workflows. The role is hands-on — you build, ship, set the bar — and is the technical counterpart to a peer EM running team scaling. You own the agentic delivery model end-to-end: orchestration patterns, evaluation harnesses, cost discipline, production safety rails. ### Responsibilities - Build and ship production agentic systems — orchestration, tool use, evaluation, observability — that go through real regulated workflows. - Set the architectural and operational standard for agentic delivery across two or three product squads; embed via review, not edict. - Author ADRs; run an open architecture-decision repository; partner with the platform team on substrate (model routing, cost telemetry, prompt-cache strategy). - Mentor staff engineers and senior engineers on agentic patterns; run an internal practice forum. - Carry a 60/40 build/leverage split — majority hands-on coding, the remainder spent shaping practice and unblocking peers. ### Must-have - 10+ years engineering experience, with 2+ years hands-on building production AI agents (LLM orchestration, tool use, memory, evaluation). - Demonstrable shipped work — links to repositories, deployed systems, or talks. CV claims alone do not pass. - Strong systems-engineering foundation — async patterns, queueing, idempotency, observability, cost telemetry. - Comfortable in regulated-domain trade-offs (data residency, auditability, model determinism, human-in-the-loop). - Operating maturity to work as IC alongside an EM peer without ambiguity. ### Nice-to-have - Prior engineering-management experience that you have deliberately stepped back from to go IC again. - Financial-services domain background (wealth, banking, capital markets). - Open-source contributions, public writing, or conference talks on agentic AI. ### Compensation indication CHF 200–240k base + meaningful equity refresh. Below-band base for a candidate with strong equity preference negotiable. --- ## 3. Head of Engineering, APAC — Wealth-Tech Scale-up (Singapore) **Location:** Singapore (on-site, relocation supported) **Level:** Head of Engineering, APAC (Senior Director equivalent) **Reporting to:** CTO (Zürich-based) ### About the role Stand up and lead the APAC engineering function for a Zürich-headquartered wealth-tech scale-up entering the Singapore and Hong Kong markets. Founding-leader role — you arrive with a near-zero local engineering footprint, an existing peer engineering team in Zürich, and a 24-month mandate to build out a 20–30 person engineering organisation co-located with the APAC business hub. ### Responsibilities - Hire the founding APAC engineering team across BE, FE, QA, and BA disciplines; design the local operating model in partnership with HQ. - Own delivery for one APAC-specific product line plus shared ownership of platform components co-developed with Zürich. - Establish working modes across time zones — async-first defaults, deliberate synchronous touchpoints, transparent decision records. - Build the local hiring brand and senior pipeline; partner with HR on locale-appropriate retention. - Run the APAC-side conversation with regulators on engineering controls (MAS, HKMA). ### Must-have - Prior experience setting up an engineering function in a new region from a near-zero base — not joining an established one. - Senior-EM or above background with 5+ years line-management experience at scope (15+ reports at some point). - Demonstrated ability to hire for attitude and learning capacity, including in markets where talent supply is constrained or expensive. - Regulated-domain delivery background — wealth management, banking, insurance, or comparable. - Willingness to relocate to Singapore for 24+ months and operate on-site as the visible local lead. ### Nice-to-have - Prior Singapore or Hong Kong work experience. - Experience operating across a Zürich ↔ APAC time-zone split inside a wealth-management business. - Bilingual capacity (English required; Mandarin, Cantonese, or Bahasa welcome). ### Compensation indication SGD 320–380k base + relocation + equity. Cost-of-living adjustment included. --- ## 4. Engineering Manager, Developer Productivity & AI Tooling — Big-Tech Engineering Centre, Zürich **Location:** Zürich (hybrid, 3 days office) **Level:** Engineering Manager (L6 equivalent) **Reporting to:** Senior Engineering Manager, Developer Experience ### About the role Lead a team of 8–12 engineers building and operating internal AI-assisted development tooling at a multinational big-tech engineering centre in Zürich. The team is the bridge between platform tooling and individual engineer experience — it ships the IDE-integrated AI assistant, the model-routing layer, internal evaluation infrastructure, and the cost-telemetry layer feeding back into procurement. ### Responsibilities - Line-manage a tenured engineering team; partner with a peer Staff IC on technical direction. - Drive the rollout and adoption of internal AI coding tooling across thousands of engineers in the Zürich centre and across the wider engineering org. - Own the evaluation harness and quality bar for AI-assisted workflows — what counts as "shipped-ready," what does not. - Operate in tight collaboration with a US-headquartered counterpart team; carry the Zürich-side perspective on tooling design. - Recruit a small contractor cohort to absorb peak workloads on tooling integrations. ### Must-have - 6+ years engineering experience with 3+ years in EM / TL-shape roles managing teams of 6+. - Hands-on AI-tooling adoption experience — either as a builder of AI dev tooling or as an EM who has led an engineering org through one. - Strong product instincts for internal-tooling customers; comfortable saying no to shiny adoption metrics in favour of real workflow change. - Track record working across time zones with a US peer. - Fluent English; German not required. ### Nice-to-have - Prior experience at a regulated-industry employer where AI tooling adoption was not trivially permitted. - Open-source or external publication footprint on AI tooling or developer experience. - Background as a former Senior IC who chose management deliberately. ### Compensation indication CHF 230–280k base + RSU package + benefits. Competitive for level at this employer shape. --- ## 5. Principal Engineer, Platform & AI Infrastructure — EU-Remote, Mid-Size Cloud-Native Company **Location:** Remote within EU / EFTA, occasional travel (≈ 4 trips/year) **Level:** Principal Engineer (IC) **Reporting to:** VP Platform Engineering ### About the role Senior-IC platform role at a 400-person, cloud-native B2B SaaS company (data infrastructure adjacent) that has been agentic-AI-curious for a year and is now committing to a production agentic platform. The role is the technical anchor of that commitment — you set the substrate, you ship the first few internal-customer applications onto it, you write the patterns the rest of the engineering org adopts. ### Responsibilities - Architect and ship the internal agentic platform (orchestration, model routing, evaluation, cost telemetry, observability) used by 5–10 product squads. - Build the first two production agentic applications onto the platform yourself; use them as the forcing function for substrate design. - Author the company-wide ADR record for AI delivery; run a fortnightly architecture forum. - Partner with a peer Principal IC on data-platform substrate; the two of you are the long-pole technical leaders. - Mentor staff and senior engineers; deliberately stay hands-on (≥ 50% code). ### Must-have - 10+ years engineering experience, including substantial time as an IC architect or platform engineer at scale. - Demonstrated shipped work in agentic AI — production systems, ideally externally visible. - Strong systems-engineering foundation; experience designing and operating multi-tenant platforms with cost and observability discipline. - Operating maturity to set direction without title-level authority; influence by review, ADR, and example. - Willingness to travel quarterly to the company's HQ (Berlin or Amsterdam). ### Nice-to-have - Prior EM or management experience you stepped back from. - Background in regulated-domain engineering (the customer base includes financial-services tenants). - Public writing or talks; a recognisable name in agentic-AI engineering circles is a plus. ### Compensation indication EUR 180–220k base + equity (real, not nominal) + remote-work allowance. --- ## 6. Head of Engineering, Investment Management Technology — Tier-1 Swiss Universal Bank **Location:** Zürich (on-site / hybrid, 3 days office) **Level:** Managing Director / Head of (Crew Lead-equivalent at internal scale) **Reporting to:** Global Head, Investment Management Technology ### About the role Lead the engineering function for the Investment Management technology crew at a tier-1 Swiss universal bank — ≈ 70 engineers, BAs, and QA across three pods, two product owners, a stream-level architect, accountable for one strategic platform and three adjacent applications serving discretionary mandate and advisory mandate workflows across four booking centres. The role owns the engineering organisation and the multi-year roadmap; product strategy is co-owned with a peer Head of Product. ### Responsibilities - Line-manage 4–6 chapter leads / team leads; own performance, hiring, succession across the crew. - Carry delivery accountability for a multi-year platform renovation (legacy rich-client + on-prem Java → modern web + cloud) and the regulatory + compliance roadmap that runs in parallel. - Set the engineering strategy for AI-assisted delivery across the crew; operate as the visible internal sponsor for adoption. - Represent the crew in stream-level and division-level governance; own escalations on cross-crew dependencies and regulatory exposures. - Partner with the Head of Product on book-of-work prioritisation and with the stream architect on target-state architecture. ### Must-have - 12+ years experience in financial-services technology, with 6+ years in senior people-management at chapter-lead-or-above scope. - Track record of delivery accountability on multi-year programmes touching multiple booking centres or regions. - Prior experience leading or being deeply embedded in a large-scale integration or platform-renovation programme. - Director / VP / MD rank or equivalent at a peer institution; credible at the Group ExBo-minus-two level. - German and English fluency. ### Nice-to-have - Prior Crew Architect or stream architect experience that informs governance-level architecture conversations. - Experience leading a chapter or team through AI-driven function compression. - Singapore / Hong Kong booking-centre exposure. ### Compensation indication CHF 280–340k base + 40–60% variable + LTI. Competitive for MD-rank IM Technology leadership in CH. --- ## 7. Director of Engineering, Platform — Cloud-Native Infrastructure Company (Zürich, Hybrid) **Location:** Zürich (hybrid, 3 days office) — global org, EU- and US-distributed peers **Level:** Director of Engineering **Reporting to:** VP Engineering (Zürich-based) ### About the role Director-level engineering leadership for the platform organisation (≈ 40 engineers across 4 teams) at a Zürich-headquartered cloud-native infrastructure company (≈ 600 engineers total, post-Series-D). The platform org provides the substrate the product engineering organisation builds on — compute, data, observability, AI tooling, security baselines. Outside financial services entirely; included deliberately to test the transferability of Stefan's domain-shape into a tech-native employer. ### Responsibilities - Line-manage 4 engineering managers; own performance, hiring, headcount planning across the platform org. - Set the 12-month platform roadmap in partnership with the product engineering directors and the VP Engineering. - Be accountable for platform reliability SLOs and developer-experience metrics. - Drive the AI-tooling track for the platform org — internal Copilot-equivalent rollout, evaluation framework, model-routing infrastructure. - Represent the platform org externally — conference talks, recruiting events, open-source community engagement (encouraged, not required). ### Must-have - 10+ years engineering experience with 5+ years at EM / Senior EM / Director scope managing managers. - Track record running a platform organisation at the 30–50 engineer range — not infrastructure-as-a-side-line, platform as the explicit lane. - Cloud-native operational depth (Kubernetes, modern observability stack, IaC, multi-region). - Strong engineering instincts; comfortable in design review on platform-level architectural decisions. - Fluent English. ### Nice-to-have - Prior experience at a cloud-native company (versus modernising a legacy stack toward cloud). - Public footprint — conference talks, recognised name in the cloud-native or platform-engineering community. - Open-source contributions to the platform-tooling ecosystem. ### Compensation indication CHF 240–290k base + equity (significant, real upside given company stage) + benefits. --- ## 8. Senior Engineering Manager, Wealth Management Engineering — Established Swiss Private Bank **Location:** Zürich (on-site / hybrid, 3 days office) **Level:** Senior Engineering Manager (Director-equivalent grade) **Reporting to:** Head of Wealth Management Engineering ### About the role Lead the engineering organisation responsible for the discretionary-mandate and advisory-mandate platform at an established Swiss private bank (smaller scale than the tier-1 universal banks but with comparable regulatory and operational rigour). Smaller-bank shape: tighter span, more direct accountability to business stakeholders, less internal political surface area. Three teams (≈ 20 engineers + BA + QA), one strategic application plus two satellites. ### Responsibilities - Line-manage 3 team leads; own performance, hiring, succession. - Co-own product roadmap with the business head for Discretionary Mandates; carry the engineering perspective into front-office conversations. - Drive a 24-month modernisation track on legacy components, sequenced against regulatory deliverables. - Lead the AI-assisted engineering practice across the org — adoption, evaluation, function evolution for BA + QA. - Run the engineering side of audit, compliance, and regulator-engagement workstreams. ### Must-have - 8+ years in financial-services technology, of which 4+ in EM / senior EM roles in wealth management or asset management. - Track record of operating with high direct accountability to front-office stakeholders. - Experience leading a legacy-to-modern modernisation track in a regulated context. - Comfortable as the visible single technical leader to non-technical executive stakeholders. - German and English fluency. ### Nice-to-have - Prior experience at a tier-1 universal bank — the contrast of bank-shape is part of the appeal of moving to a smaller institution. - Hands-on AI-assisted engineering practice and a clear point of view on its implications for BA + QA functions. - Prior product-ownership or programme-lead experience alongside line management. ### Compensation indication CHF 210–250k base + 20–30% variable. Pension, profit-share, and benefits per CH private-banking norm. --- END OF PROMPT --- That's the whole exercise. Your output should open with the boundary line and then deliver Part 1, Part 2, and Part 3 in order.