chore: add Swisscom SW-7 data mesh achievement, Google FDE drafts, scout perms

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

JDs/temp_google_fde_genai.txt

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+Senior Forward Deployed Engineer, GenAI, Google Cloud
+Google — Go-To-Market team, Google Cloud
+Locations: Vienna, Austria; Zürich, Switzerland; Berlin, Germany; Hamburg, Germany; Munich, Germany
+Level: Mid
+URL: https://www.google.com/about/careers/applications/jobs/results/98998917743420102-senior-forward-deployed-engineer-genai-google-cloud
+
+Minimum qualifications:
+- Bachelor's degree in Engineering, Computer Science, a related field, or equivalent practical experience.
+- 6 years of experience building and shipping production-grade AI-driven solutions to external or internal customers using Python, Typescript or comparable languages.
+- Experience leading technical discovery sessions with business stakeholders and engineering teams to define AI and hardware infrastructure requirements.
+- Experience designing and building AI systems on cloud platforms (e.g., Google Cloud Platform (GCP)).
+- Experience building pipelines for structured, unstructured data, incorporating vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise-grade AI solutions.
+
+Preferred qualifications:
+- Master's degree or PhD in AI, Computer Science, or a related technical field.
+- Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google's Agent Development Kit (ADK)) and patterns like ReAct, self-reflection, and hierarchical delegation.
+- Knowledge of large language model native metrics (tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
+
+About the job:
+As a GenAI Forward Deployed Engineer at Google Cloud, you will be an embedded builder bridging the gap between frontier AI products and production-grade reality for our customers. You will function as a builder-consultant, moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer's environment.
+
+In this role, you will manage blockers to production including solving the integration complexities, data readiness issues, and state-management issues that prevent AI from reaching enterprise-grade maturity. By embedding with accounts, you will serve a dual purpose: providing white-glove deployment of AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud's future product roadmap.
+
+It's an exciting time to join Google Cloud's Go-To-Market team, leading the AI revolution for businesses worldwide. We'll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform. We're a collaborative culture providing direct access to DeepMind's engineering and research minds.
+
+Responsibilities:
+- Serve as the lead developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol servers) that drive measurable return on investment.
+- Architect and code the connective tissue between Google's AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters.
+- Build high-quality, production-grade solutions, providing white-glove deployment and acting as a feedback loop into Google Cloud's product roadmap.
+- Lead technical discovery with business stakeholders and engineering teams to define AI and infrastructure requirements.
+- Optimize LLM-native metrics (tokens/sec, cost-per-request), state management, and granular tracing.